A. Yuille

发表

Fingerprints theorems for zero crossings

T. Poggio, A. Yuille, 1985 .

Deformable Templates for Face Recognition

A. Yuille, 1991, Journal of Cognitive Neuroscience.

Spontaneous symmetry-breaking energy functions and the emergence of orientation selective cortical cells

A. Yuille, D. Kammen, 2004, Biological Cybernetics.

Object perception as Bayesian inference.

A. Yuille, D. Kersten, P. Mamassian, 2004, Annual review of psychology.

Opinion TRENDS in Cognitive Sciences Vol.10 No.7 July 2006 Special Issue: Probabilistic models of cognition Vision as Bayesian inference: analysis by synthesis?

A. Yuille, D. Kersten, 2022 .

Image Parsing: Unifying Segmentation, Detection, and Recognition

Zhuowen Tu, Alan L. Yuille, Song-Chun Zhu, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

Two- and Three-Dimensional Patterns of the Face

A. Yuille, G. Gordon, B. Herbst, 2001 .

Towards Unified Object Detection and Semantic Segmentation

Jian Dong, Qiang Chen, Shuicheng Yan, 2014, ECCV.

Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation

George Papandreou, Kevin P. Murphy, Alan L. Yuille, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Learning Deep Structured Models

Alan L. Yuille, Raquel Urtasun, Alexander G. Schwing, 2014, ICML.

A Double-Loop Algorithm to Minimize the Bethe and Kikuchi Free Energies

A. Yuille, 2001 .

The Role of Context for Object Detection and Semantic Segmentation in the Wild

Sanja Fidler, Roozbeh Mottaghi, Alan L. Yuille, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Are Labels Necessary for Neural Architecture Search? pdf

Chenxi Liu, Alan Yuille, Kaiming He, 2020, ECCV.

Bayesian generic priors for causal learning.

A. Yuille, K. Holyoak, P. Cheng, 2008, Psychological review.

Latent hierarchical structural learning for object detection

William T. Freeman, Long Zhu, Yuanhao Chen, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Bottom-Up Segmentation for Top-Down Detection

Sanja Fidler, Roozbeh Mottaghi, Alan L. Yuille, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Unsupervised Learning of Probabilistic Grammar-Markov Models for Object Categories

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Image Parsing: Unifying Segmentation, Detection, and Recognition

Zhuowen Tu, Alan L. Yuille, Song-Chun Zhu, 2005, International Journal of Computer Vision.

DeePM: A Deep Part-Based Model for Object Detection and Semantic Part Localization pdf

Jun Zhu, Alan L. Yuille, Xianjie Chen, 2015, ArXiv.

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs pdf

Iasonas Kokkinos, George Papandreou, Alan L. Yuille, 2014, ICLR.

A generalized ordering constraint for stereo correspondence

T. Poggio, A. Yuille, 1984 .

The Convergence of Contrastive Divergences

Alan L. Yuille, A. Yuille, 2004, NIPS.

Efficient Deformable Template Detection and Localization without User Initialization

Daniel Snow, Alan L. Yuille, James M. Coughlan, 2000, Comput. Vis. Image Underst..

Statistical Physics, Mixtures of Distributions, and the EM Algorithm

Alan L. Yuille, Joachim Utans, Paul E. Stolorz, 1994, Neural Computation.

Feature extraction from faces using deformable templates

Alan L. Yuille, David S. Cohen, Peter W. Hallinan, 2004, International Journal of Computer Vision.

Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

Wei Xu, Jiang Wang, Yi Yang, 2014, ICLR.

The Concave-Convex Procedure

Alan L. Yuille, Anand Rangarajan, A. Yuille, 2003, Neural Computation.

A regularized solution to edge detection

Alan L. Yuille, Tomaso A. Poggio, Harry Voorhees, 1985, J. Complex..

A Regularized Solution To Edge Detection AI Memo

T. Poggio, A. Yuille, H. Voorhees, 2022 .

Scaling Theorems for Zero Crossings

Alan L. Yuille, Tomaso A. Poggio, T. Poggio, 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

The Motion Coherence Theory

Alan L. Yuille, Norberto M. Grzywacz, A. Yuille, 1988, [1988 Proceedings] Second International Conference on Computer Vision.

Rigidity and Smoothness of Motion

S. Ullman, A. Yuille, 1987 .

Energy functions for early vision and analog networks

A. Yuille, Alan L. Yuille, A. L. Yuille, 1989, Biological Cybernetics.

Special issue on “Probabilistic models of cognition

J. Tenenbaum, A. Yuille, N. Chater, 2022 .

Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2006, NIPS.

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Iasonas Kokkinos, George Papandreou, Alan L. Yuille, 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Progressive Neural Architecture Search

Li Fei-Fei, Chenxi Liu, Wei Hua, 2017, ECCV.

Dense Scale Invariant Descriptors for Images and Surfaces

A. Yuille, M. Bronstein, I. Kokkinos, 2012 .

Explain Images with Multimodal Recurrent Neural Networks pdf

Wei Xu, Jiang Wang, Yi Yang, 2014, ArXiv.

Part and appearance sharing: Recursive Compositional Models for multi-view

Antonio Torralba, William T. Freeman, Long Zhu, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Inference and Learning with Hierarchical Shape Models

Iasonas Kokkinos, Alan L. Yuille, A. Yuille, 2011, International Journal of Computer Vision.

The Concave-Convex Procedure (CCCP)

Alan L. Yuille, Anand Rangarajan, A. Yuille, 2001, NIPS.

Statistical cues for domain specific image segmentation with performance analysis

Alan L. Yuille, Scott Konishi, A. Yuille, 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation

Alan L. Yuille, Song-Chun Zhu, A. Yuille, 1996, IEEE Trans. Pattern Anal. Mach. Intell..

Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation pdf

George Papandreou, Alan L. Yuille, Kevin Murphy, 2015, ArXiv.

Analog "neuronal" networks in early vision.

C Koch, J Marroquin, A Yuille, 1986, Proceedings of the National Academy of Sciences of the United States of America.

Manhattan World: Orientation and Outlier Detection by Bayesian Inference

James M. Coughlan, A. L. Yuille, A. Yuille, 2003, Neural Computation.

An Analysis of the Elastic Net Approach to the Traveling Salesman Problem

Richard Szeliski, Alan L. Yuille, Richard Durbin, 1989, Neural Computation.

A model for the estimate of local image velocity by cells in the visual cortex

A. Yuille, N. Grzywacz, 1990, Proceedings of the Royal Society of London. B. Biological Sciences.

Deformable templates

Alan L. Yuille, Peter L. Hallinan, A. Yuille, 1993 .

Deformable Templates for Feature Extraction from Medical Images

Alan L. Yuille, P. Lipson, D. O'Keeffe, 1990, ECCV.

Region competition: unifying snakes, region growing, energy/Bayes/MDL for multi-band image segmentation

Tai Sing Lee, Alan L. Yuille, Song Chun Zhu, 1995, Proceedings of IEEE International Conference on Computer Vision.

Bayesian A Tree Search with Expected O(N) Node Expansions: Applications to Road Tracking

Alan L. Yuille, James M. Coughlan, A. Yuille, 2002, Neural Computation.

Probabilistic models of cognition. Special Issue.

J. Tenenbaum, A. Yuille, N. Chater, 2006 .

Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform

Jonathan T. Barron, George Papandreou, Alan L. Yuille, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Gaussian sampling by local perturbations

George Papandreou, Alan L. Yuille, A. Yuille, 2010, NIPS.

Dimension reduction, generalized deformable models and the development of occularity and orientation

A. Yuille, J. Kolodny, C. W. Lee, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Adversarial Attacks Beyond the Image Space

Chenxi Liu, Alan L. Yuille, Chi-Keung Tang, 2017, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Technical Introduction: A primer on probabilistic inference

Thomas L. Griffiths, Alan L. Yuille, A. Yuille, 2005 .

Bayesian decision theory and psychophysics

A. Yuille, H. Bülthoff, 1996 .

A Theoretical Framework for Visual Motion

A. Yuille, Norberto M. GrzywaczSmith-Kettlewell, 1996 .

Deep networks under scene-level supervision for multi-class geospatial object detection from remote sensing images

Xin Huang, Yongjun Zhang, Yansheng Li, 2018, ISPRS Journal of Photogrammetry and Remote Sensing.

Generalized Deformable Models, Statistical Physics, and Matching Problems

Alan L. Yuille, A. Yuille, 1990, Neural Computation.

Track finding with deformable templates — the elastic arms approach

A. Yuille, C. Peterson, M. Ohlsson, 1992 .

CCCP Algorithms to Minimize the Bethe and Kikuchi Free Energies: Convergent Alternatives to Belief Propagation

Alan L. Yuille, A. Yuille, 2002, Neural Computation.

Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian Model Classification

Alan L. Yuille, Jason J. Corso, Suzie El-Saden, 2008, IEEE Transactions on Medical Imaging.

Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Shape Matching and Recognition - Using Generative Models and Informative Features

Zhuowen Tu, Alan L. Yuille, A. Yuille, 2004, ECCV.

Statistical Edge Detection: Learning and Evaluating Edge Cues

Alan L. Yuille, Song-Chun Zhu, James M. Coughlan, 2003, IEEE Trans. Pattern Anal. Mach. Intell..

Learning Object Representations from LightingVariationsR

P. Belhumeur, A. Yuille, .. Epstein, 1996 .

UnrealCV: Connecting Computer Vision to Unreal Engine

Alan L. Yuille, Weichao Qiu, A. Yuille, 2016, ECCV Workshops.

The invisible hand algorithm: Solving the assignment problem with statistical physics

Alan L. Yuille, J. J. Kosowsky, A. Yuille, 1994, Neural Networks.

A common framework for image segmentation

A. Yuille, D. Geiger, A. Yuille, 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

AdaBoost Learning for Detecting and Reading Text in City Scenes

Alan L. Yuille, Xiangrong Chen, A. Yuille, 2004, CVPR 2004.

A common framework for image segmentation

Alan L. Yuille, Davi Geiger, A. Yuille, 1990, International Journal of Computer Vision.

Fingerprints Theorems

Alan L. Yuille, Tomaso A. Poggio, T. Poggio, 1984, AAAI.

FORMS: A flexible object recognition and modelling system

Alan L. Yuille, Song-Chun Zhu, A. Yuille, 1996, International Journal of Computer Vision.

Deformable templates, robust statistics, and Hough transforms

Carsten Peterson, Alan L. Yuille, Ko Honda, 1991, Optics & Photonics.

Perturb-and-MAP random fields: Using discrete optimization to learn and sample from energy models

George Papandreou, Alan L. Yuille, A. Yuille, 2011, 2011 International Conference on Computer Vision.

Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking

Alan L. Yuille, James M. Coughlan, A. Yuille, 2000, IEEE Trans. Pattern Anal. Mach. Intell..

Cross-Iteration Batch Normalization

A. Yuille, K. Murphy, Gao Huang, 2019, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Winner-Take-All Mechanism Based on Presynaptic Inhibition Feedback

Alan L. Yuille, Norberto M. Grzywacz, A. Yuille, 1989, Neural Computation.

Motion estimation by Swendsen-Wang Cuts

A. Yuille, Adrian Barbu, 2004, CVPR 2004.

Statistical Physics Algorithms That Converge

J. J. Kosowsky, A. L. Yuille, A. Yuille, 1994, Neural Computation.

Towards unified depth and semantic prediction from a single image

Alan L. Yuille, Zhe L. Lin, Scott Cohen, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

A method for computing spectral reflectance

A. Yuille, 1987, Biological Cybernetics.

An Extremum Principle for Shape from Contour

Alan L. Yuille, Michael Brady, A. Yuille, 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Perspective Projection Invariants

A. Verri, A. Yuille, 1986 .

5/spl plusmn/2 eigenimages suffice: an empirical investigation of low-dimensional lighting models

Russell A. Epstein, Alan L. Yuille, Peter W. Hallinan, 1995, Proceedings of the Workshop on Physics-Based Modeling in Computer Vision.

Manhattan World: compass direction from a single image by Bayesian inference

Alan L. Yuille, James M. Coughlan, A. Yuille, 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

Generation and Comprehension of Unambiguous Object Descriptions

Alan L. Yuille, Kevin Murphy, Junhua Mao, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

An Approach to Pose-Based Action Recognition

Alan L. Yuille, Chunyu Wang, Yizhou Wang, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Detecting and reading text in natural scenes

Alan L. Yuille, Xiangrong Chen, A. Yuille, 2004, CVPR 2004.

Fundamental bounds on edge detection: an information theoretic evaluation of different edge cues

Alan L. Yuille, Song-Chun Zhu, James M. Coughlan, 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

The DLR Hierarchy of Approximate Inference pdf

Michael I. Jordan, Alan L. Yuille, Michal Rosen-Zvi, 2005, UAI.

Recursive segmentation and recognition templates for image parsing

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Local, global, and multilevel stereo matching

Alan L. Yuille, Jie Lu, Yibing Yang, 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

Boundary Detection Benchmarking: Beyond F-Measures

Christof Koch, Alan L. Yuille, Xiaodi Hou, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

On radial basis function nets and kernel regression: Statistical consistency, convergence rates, and receptive field size

Adam Krzyzak, Alan L. Yuille, Lei Xu, 1994, Neural Networks.

On Radial Basis Function Net and Kernel Regression: Approximation Ability, Convergence Rate and Receptive Field Size

A. Krzyżak, A. Yuille, Lei Xu, 1993, Proceedings. IEEE International Symposium on Information Theory.

Feature extraction from faces using deformable templates

Alan L. Yuille, David S. Cohen, Peter W. Hallinan, 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

The Bas-Relief Ambiguity

David J. Kriegman, Alan L. Yuille, Peter N. Belhumeur, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Describing surfaces

Jean Ponce, Alan L. Yuille, Michael Brady, 1985, Comput. Vis. Graph. Image Process..

Representing Three-dimensional Shape

A. Yuille, M. Brady, 1985 .

Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model

Tai Sing Lee, Alan L. Yuille, David Mumford, 1992, ECCV.

Convergence Properties of the Softassign Quadratic Assignment Algorithm

Alan L. Yuille, Eric Mjolsness, Anand Rangarajan, 1999, Neural Computation.

Active Vision

Alan Yuille, Andrew Blake, A. Yuille, 2014, Computer Vision, A Reference Guide.

Adversarial Examples for Semantic Segmentation and Object Detection

Alan L. Yuille, Yuyin Zhou, Zhishuai Zhang, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Probabilistic models of cognition: where next?

J. Tenenbaum, A. Yuille, N. Chater, 2006, Trends in Cognitive Sciences.

Transfer of View-manifold Learning to Similarity Perception of Novel Objects pdf

Hao Wang, Tai Sing Lee, Alan L. Yuille, 2017, ICLR.

Efficient Coding of Visual Scenes by Grouping and Segmentation: Theoretical Predictions and Biological Evidence

Tai Sing Lee, Alan L. Yuille, A. Yuille, 2006 .

Recurrent Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Small Organ Segmentation

Alan L. Yuille, Qihang Yu, Yuyin Zhou, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Regularizing Face Net For Discrete-Valued Pain Regression

A. Yuille, Gregory Hager, T. Tran, 2017 .

Functional form of motion priors in human motion perception

Alan L. Yuille, Hongjing Lu, Luminita A. Vese, 2010, NIPS.

Scale invariance without scale selection

Iasonas Kokkinos, Alan L. Yuille, A. Yuille, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Augmented Rescorla-Wagner and Maximum Likelihood Estimation

Alan L. Yuille, A. Yuille, 2005, NIPS.

Learning Like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images

Xu Wei, Alan L. Yuille, Zhiheng Huang, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Genetic CNN

Alan L. Yuille, Lingxi Xie, A. Yuille, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Detecting Object Boundaries Using Low-, Mid-, and High-level Information

Zhuowen Tu, Alan L. Yuille, Songfeng Zheng, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Detection and Segmentation of Pathological Structures by the Extended Graph-Shifts Algorithm

Arthur W. Toga, Alan L. Yuille, Jason J. Corso, 2007, MICCAI.

Multi-Scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma

Alan L. Yuille, Yingda Xia, Elliot K. Fishman, 2018, MICCAI.

Computer vision needs a core and foundations

Alan L. Yuille, A. Yuille, 2012, Image and Vision Computing.

Impossible Shaded Images

Richard Szeliski, Alan L. Yuille, Berthold K. P. Horn, 1993, IEEE Trans. Pattern Anal. Mach. Intell..

Discovering Internal Representations from Object-CNNs Using Population Encoding pdf

Alan L. Yuille, Zhishuai Zhang, Jianyu Wang, 2015, ArXiv.

DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

Xiang Bai, Alan Yuille, Wei Shen, 2016, IEEE Transactions on Image Processing.

The Statistics of Natural Scenes and the Inference of 3 D Shape Thesis Proposal

A. Yuille, M. Lewicki, 2006 .

Bottom-Up Processing in Complex Scenes: A Unifying Perspective on Segmentation, Fixation Saliency, Candidate Regions, Base-Detail Decomposition, and Image Enhancement

A. Yuille, B. Bonev, 2015 .

A Part-Based, Multiresolution, TensorFaces Approach to Image-Based Facial Veriﬁcation

M. Alex O. Vasilescu, A. Yuille, Demetri Terzopoulos, 2016 .

Fast AdvProp

Cihang Xie, A. Yuille, Yingwei Li, 2022, ICLR.

Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

A. Yuille, Liang-Chieh Chen, Hartwig Adam, 2020, ECCV.

Electronic Theses and Dissertations Title Mining Spatial and Spatio-Temporal ROIs for Action Recognition Permalink

A. Yuille, Xiaochen Lian, Qing Zhou, 2016 .

SAFER : Fine-grained Activity Detection by Compositional Hypothesis Testing

Tae Soo Kim, A. Yuille, Gregory Hager, 2019 .

Computational Vision : Principles of Perceptual Inference ∗

A. Yuille, D. Kersten, J. Coughlan, 1998 .

Memo No . 082 May 10 , 2018 Scene Graph Parsing as Dependency Parsing

A. Yuille, Chenxi Liu, Yu-Siang Wang, 2018 .

Attention to Scale: Scale-Aware Semantic Image Segmentation

Yi Yang, Alan L. Yuille, Liang-Chieh Chen, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Thickened 2 D Networks for 3 D Medical Image Segmentation

A. Yuille, E. Fishman, Lingxi Xie, 2019 .

1 Basic Concepts and Overview

A. Yuille, D. Kersten, 2015 .

Object Boundary Detection and Foreground / Background Segmentation by Integrating Information from Low-level to High-level ∗

A. Yuille, Songfeng Zheng, 2007 .

Title Scale Invariance without Scale Selection Permalink

A. Yuille, I. Kokkinos, Iasonas Kokkinos, 2008 .

Action as an innate bias for visual learning

A. Yuille, H. Bülthoff, 2012, Proceedings of the National Academy of Sciences.

Learning from Temporal Gradient for Semi-supervised Action Recognition

A. Yuille, Junfei Xiao, Longlong Jing, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Utility of CT Radiomics Features in Differentiation of Pancreatic Ductal Adenocarcinoma From Normal Pancreatic Tissue.

A. Yuille, Seyoun Park, L. Chu, 2019, AJR. American journal of roentgenology.

→ " Y " N X " Generation N Y " X " Inference ( segmentation ) X " → $ X " → $ X " →

A. Yuille, E. Fishman, Lingxi Xie, 2019 .

Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation pdf

Yan Wang, Yingwei Li, Yuyin Zhou, 2019, MICCAI.

Title A Bayesian Network Framework for Relational Shape Matching Permalink

A. Yuille, J. Coughlan, Anand Rangarajan, 2003 .

Shape-Texture Debiased Neural Network Training pdf

Yingwei Li, Qihang Yu, Alan Yuille, 2020, ICLR.

Deep Learning in Radiology: Now the Real Work Begins.

A. Yuille, B. Vogelstein, E. Fishman, 2018, Journal of the American College of Radiology : JACR.

Smooth Adversarial Training

Quoc V. Le, Cihang Xie, Mingxing Tan, 2020, ArXiv.

DRAFT 3 / 4 / 07 Bayesian Generic Priors for Causal Learning

A. Yuille, K. Holyoak, P. Cheng, 2007 .

Bayesian Models of Judgments of Causal Strength: A Comparison

A. Yuille, K. Holyoak, P. Cheng, 2007 .

Probabilistic Models of Cogntion: Conceptual Foundations

J. Tenenbaum, A. Yuille, N. Chater, 2006 .

Mitigating adversarial effects through randomization pdf

Alan L. Yuille, Zhishuai Zhang, Jianyu Wang, 2017, ICLR.

Inferential Models of the Visual Cortical Hierarchy*

A. Yuille, D. Kersten, 2013 .

Lecture 12: Binocular Stereo and Belief Propagation

A. Yuille, 2012 .

Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience.

Yan Wang, Yingda Xia, Qihang Yu, 2019, Journal of the American College of Radiology : JACR.

Annotated normal CT data of the abdomen for deep learning: Challenges and strategies for implementation.

A. Yuille, Seyoun Park, L. Chu, 2019, Diagnostic and interventional imaging.

cation of spatially unaligned fMRI scans

Ariana E. Anderson, Mark S. Cohen, A. Yuille, 2009 .

Title Vision as Bayesian Inference : Analysis by Synthesis ?

A. Yuille, D. Kersten, 2006 .

Memo No . 85 06 / 2018 Deep Regression Forests for Age Estimation

A. Yuille, Wei Shen, Yan Wang, 2018 .

mpetition: Unifying Snakes, egion Growin and Bayes/MDL for Image Segmentation

A. Yuille, Song-Chun Zhu, 1996 .

Title Probabilistic Models of Cognition : Where Next ?

J. Tenenbaum, A. Yuille, N. Chater, 2006 .

Cue Coupling

A. Yuille, D. Kersten, 2013 .

Arbib Chapter : Lecture 5 . Modules and Cue Coupling

A. Yuille, D. Kersten, 2022 .

The perceived motion of a stereokinetic stimulus

A. Yuille, Zili Liu, B. Rokers, 2006, Vision Research.

Title Bayesian Models of Object Perception

A. Yuille, D. Kersten, 2003 .

Spontaneous symmetry-breaking energy functionsand the emergence of orientation selective cortical cells

D. M. Kammen, A. L. Yuille, A. Yuille, 1988, Biological Cybernetics.

Title AdaBoost Learning for Detecting and Reading Text in City Scenes Permalink

A. Yuille, Xiangrong Chen, 2004 .

Ad-a131 321 an Extremum Principle. For. Shape from Contour(u)

A. Yuille, M. Brady, 2022 .

Shape from Shading, Occlusion and Texture

A. Yuille, 1992 .

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features.

A. Yuille, Seyoun Park, E. Fishman, 2020, Diagnostic and interventional imaging.

Dependence of speed and direction perception on cinematogram dot density

Scott N. J. Watamaniuk, Alan L. Yuille, Norberto M. Grzywacz, 1993, Vision Research.

Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Yukun Zhu, Alan Yuille, Liang-Chieh Chen, 2020, ECCV.

Title A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci Permalink

Agatha D. Lee, A. Yuille, Z. Tu, 2006 .

Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots

A. Yuille, K. Jia, Lin Sun, 2019, ECCV.

Toward visual primal sketches

Jean Ponce, Haruo Asada, Michael Brady, 1985, Annual Meeting Optical Society of America.

Diagnostic performance of commercially available vs. in-house radiomics software in classification of CT images from patients with pancreatic ductal adenocarcinoma vs. healthy controls

A. Yuille, Seyoun Park, L. Chu, 2020, Abdominal Radiology.

Transferring a Face Verification Network for Expression Intensity Regression

Gregory D. Hager, Austin Reiter, Trac D. Tran, 2017 .

Title A Time-Efficient Cascade for Real-Time Object Detection : With applications for the visually impaired Permalink

A. Yuille, 2007 .

The Bas-Relief Ambiguity

P. Belhumeur, A. Yuille, D. Kriegman, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Larger organ size caused by obesity is a mechanism for higher cancer risk

A. Yuille, Seyoun Park, L. Chu, 2020, bioRxiv.

Organ size increases with obesity and correlates with cancer risk

A. Yuille, Seyoun Park, L. Chu, 2020, 2005.13112.

N E M O : N EURAL M ESH M ODELS OF C ONTRASTIVE F EATURES FOR R OBUST 3D P OSE E STIMATION

A. Yuille, Angtian Wang, Adam Kortylewski, 2021 .

A large deviation theory analysis of Bayesian tree search

Alan L. Yuille, James M. Coughlan, A. Yuille, 2003 .

CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT

Yixiao Zhang, David Dreizin, Yuyin Zhou, 2019, Journal of Digital Imaging.

Erratum to "Annotated normal CT data of the abdomen for deep learning: Challenges and strategies for implementation" [Diagn. Interv. Imaging. 101 (2020) 35-44].

A. Yuille, L. Chu, K. Kinzler, 2020, Diagnostic and interventional imaging.

A Simple Data Mixing Prior for Improving Self-Supervised Learning

Cihang Xie, A. Yuille, Yuyin Zhou, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In Defense of Online Models for Video Instance Segmentation

A. Yuille, S. Bai, Xiang Bai, 2022, ECCV.

Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition

Alan L. Yuille, Anand Rangarajan, Baba C. Vemuri, 2005 .

Occluded Video Instance Segmentation: A Benchmark

Philip H. S. Torr, Serge J. Belongie, A. Yuille, 2021, International Journal of Computer Vision.

k-means Mask Transformer

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022, ECCV.

ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation pdf

Alan Yuille, Siyuan Qiao, Liang-Chieh Chen, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Statistical and Geometrical Approaches to Visual Motion Analysis, International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008. Revised Papers

Bodo Rosenhahn, Daniel Cremers, Frank R. Schmidt, 2009, Lecture Notes in Computer Science.

Explicit Occlusion Reasoning for Multi-person 3D Human Pose Estimation

A. Yuille, S. Bai, Yi Zhang, 2022, ECCV.

Efficient Coding of Visual Scenes by Groupoing and Segmentation: Theoretical Predictions and Biological Evidence

A. Yuille, T. Lee, 2005 .

In Defense of Image Pre-Training for Spatiotemporal Recognition

Cihang Xie, A. Yuille, Yuyin Zhou, 2022, ArXiv.

Amodal Segmentation through Out-of-Task and Out-of-Distribution Generalization with a Bayesian Model

A. Yuille, Adam Kortylewski, Yihong Sun, 2020, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Light-weight Interpretable Compositional Model for Nuclei Detection and Weakly-Supervised Segmentation

A. Yuille, Seyoun Park, J. Taube, 2021, 2110.13846.

The Creation Of Structure In Dynamic Shape

Alan L. Yuille, A. Yuille, 1988, [1988 Proceedings] Second International Conference on Computer Vision.

Parsing: Unifying Segmentation, Detection, and Recognition

A. Yuille, Song-Chun Zhu, Xiangrong Chen, 2005 .

Robust Category-Level 6D Pose Estimation with Coarse-to-Fine Rendering of Neural Features

A. Yuille, Angtian Wang, Adam Kortylewski, 2022, ECCV.

Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement

Bingbing Ni, Alan Yuille, Zefan Li, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation

A. Yuille, Wei Shen, Huiyu Wang, 2022, ECCV.

Simulated Adversarial Testing of Face Recognition Models

Sarah Adel Bargal, Cihang Xie, A. Yuille, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Thickened 2D Networks for Efficient 3D Medical Image Segmentation.

A. Yuille, E. Fishman, Lingxi Xie, 2019, 1904.01150.

Making Your First Choice: To Address Cold Start Problem in Vision Active Learning

A. Yuille, B. Wen, Yongyi Lu, 2022, ArXiv.

MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models

A. Yuille, Liang-Chieh Chen, Hartwig Adam, 2022, 2210.01820.

OOD-CV: A Benchmark for Robustness to Individual Nuisances in Real-World Out-of-Distribution Shifts

A. Yuille, Ju He, Angtian Wang, 2021 .

Intriguing Properties of Adversarial Training at Scale

Cihang Xie, A. Yuille, 2019, ICLR.

Israel-Wilson metrics in the Euclidean regime

A. Yuille, 1987 .

Yang-Mills instantons in self-dual spacetimes

A. Yuille, 1979 .

Winner-take-all mechanisms

Alan L. Yuille, Davi Geiger, Alan L. Yuille, 1998 .

Motion Modeis : Part I

A. Yuille, D. Kersten, 2013 .

Ideal Observers for Detecting Human Motion: Correspondence Noise

A. Yuille, HongJing Lo, 2011 .

VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis

A. Yuille, Jian Sun, Angtian Wang, 2022, ArXiv.

OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

A. Yuille, Ju He, Angtian Wang, 2021, ECCV.

Effective Pancreatic Cancer Screening on Non-contrast CT Scans via Anatomy-Aware Transformers

Le Lu, Alan L. Yuille, Yingda Xia, 2021, MICCAI.

Masked Autoencoders Enable Efficient Knowledge Distillers

Cihang Xie, A. Yuille, Yuyin Zhou, 2022, ArXiv.

k-means Mask Transformer

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022, ECCV.

Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification

A. Yuille, Yutong Bai, Junfei Xiao, 2022, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Smooth Adversarial Training

Quoc V. Le, Cihang Xie, Mingxing Tan, 2020, ArXiv.

Synthetic Tumors Make AI Segment Tumors Better

A. Yuille, Junfei Xiao, Zongwei Zhou, 2022, ArXiv.

Masked Autoencoders Enable Efficient Knowledge Distillers

Cihang Xie, A. Yuille, Yuyin Zhou, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In Defense of Image Pre-Training for Spatiotemporal Recognition

Cihang Xie, A. Yuille, Yuyin Zhou, 2022, ECCV.

Appendix for k -means Mask Transformer

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022 .

Supplementary Materials: ”TransMix: Attend to Mix for Vision Transformers”

Philip H. S. Torr, A. Yuille, Shuyang Sun, 2022 .

Coarse-To-Fine Incremental Few-Shot Learning - Appendix

A. Yuille, Xiang Xiang, Yuwen Tan, 2022 .

1st Place Solution of The Robust Vision Challenge (RVC) 2022 Semantic Segmentation Track

A. Yuille, Anima Anandkumar, Zhiding Yu, 2022, ArXiv.

Recovering the functional form of the slow-and-smooth prior in global motion perception

Alan L. F. Lee, A. Yuille, L. Vese, 2010 .

SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training

Cihang Xie, A. Yuille, Huiyu Wang, 2022, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

Progressive Neural Architecture Search ( Supplementary Material )

Li Fei-Fei, Chenxi Liu, Alan Yuille, 2018 .

CoKe: Localized Contrastive Learning for Robust Keypoint Detection

A. Yuille, Yutong Bai, Angtian Wang, 2020, ArXiv.

Deep Nets: What have They Ever Done for Vision?

A. Yuille, Chenxi Liu, 2020, International Journal of Computer Vision.

CORL: Compositional Representation Learning for Few-Shot Classification

A. Yuille, Ju He, Adam Kortylewski, 2021, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Image Parsing: Unifying Segmentation, Detection, and Recognition

A. Yuille, Song-Chun Zhu, Z. Tu, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

Title A Hierarchical Compositional System for Rapid Object Detection Permalink

A. Yuille, Long Zhu, 2005 .

A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation pdf

Nuno Vasconcelos, Weichao Qiu, Alan Yuille, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers

A. Yuille, Liang-Chieh Chen, Hartwig Adam, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

LUMix: Improving Mixup by Better Modelling Label Uncertainty

Philip H. S. Torr, A. Yuille, Ruifei He, 2022, ArXiv.

Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition

Daniel Cremers, Alan L. Yuille, Song-Chun Zhu, 2007 .

A hierarchical Bayesian model of causal learning in humans and rats

Hongjing Lu, Tom Beckers, Alan L. Yuille, 2008 .

Superior perception of circular/radial than translational motion cannot be explained by generic priors

Hongjing Lu, Alan Lap-fai Lee, Alan L. Yuille, 2010 .

Title Model Selection and Velocity Estimation Using Novel Priors for Motion Patterns Permalink

A. Yuille, Hongjing Lu, Shuang Wu, 2009 .

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

A. Yuille, Yixuan Yuan, Yongyi Lu, 2023, ArXiv.

3D symmetry-curvature duality theorems

Alan L. Yuille, Michael Leyton, A. Yuille, 1990, Comput. Vis. Graph. Image Process..

Zero crossings on lines of curvature

A.L Yuille, A. Yuille, 1989, Comput. Vis. Graph. Image Process..

Probabilistic Theories of the Visual Cortex

A. Yuille, D. Kersten, See Carandini, 2013 .

Deep learning-based quantitative visualization and measurement of extraperitoneal hematoma volumes in patients with pelvic fractures: Potential role in personalized forecasting and decision support.

A. Yuille, D. Dreizin, Guang Li, 2020, The journal of trauma and acute care surgery.

Deep Nets: What have They Ever Done for Vision? pdf

Chenxi Liu, Alan L. Yuille, A. Yuille, 2018, International Journal of Computer Vision.

Neural Architecture Search for Lightweight Non-Local Networks

Yingwei Li, Qihang Yu, Yuyin Zhou, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Robust principal component analysis by self-organizing rules based on statistical physics approach

Alan L. Yuille, Lei Xu, A. Yuille, 1995, IEEE Trans. Neural Networks.

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

A. Yuille, H. Roth, Qihang Yu, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Dimension reduction, generalized deformable models and the development of ocularity and orientation

Alan L. Yuille, C. W. Lee, James A. Kolodny, 1996, Neural Networks.

Deep Distance Transform for Tubular Structure Segmentation in CT Scans

Yan Wang, Wei Shen, Yuyin Zhou, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

SURGE: Surface Regularized Geometry Estimation from a Single Image

Alan L. Yuille, Scott Cohen, Brian L. Price, 2016, NIPS.

A computational theory for the perception of coherent visual motion

Norberto M. Grzywacz, Alan L. Yuille, A. Yuille, 1988, Nature.

Robust 3D Human Pose Estimation from Single Images or Video Sequences

Alan L. Yuille, Chunyu Wang, Yizhou Wang, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Robust Estimation of 3D Human Poses from a Single Image

Wen Gao, Alan L. Yuille, Chunyu Wang, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Exploiting Protrusion Cues for Fast and Effective Shape Modeling via Ellipses

Brian Taylor, Alan L. Yuille, Alex Wong, 2017, BMVC.

One Shot Learning via Compositions of Meaningful Patches

Alan L. Yuille, Alex Wong, A. Yuille, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Segmenting by seeking the symmetry axis

Alan L. Yuille, Tyng-Luh Liu, Davi Geiger, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

FORMS: A flexible object recognition and modelling system

Alan L. Yuille, Song-Chun Zhu, A. Yuille, 1995, Proceedings of IEEE International Conference on Computer Vision.

Constrained optimization and the elastic net

Alan L. Yuille, A. Yuille, 1998 .

Introduction: a Bayesian formulation of visual perception

David C. Knill, Daniel Kersten, Alan L. Yuille, 1996 .

Robust Point Matching via Vector Field Consensus

Zhuowen Tu, Alan L. Yuille, Ji Zhao, 2014, IEEE Transactions on Image Processing.

A mathematical analysis of the motion coherence theory

Alan L. Yuille, Norberto M. Grzywacz, A. Yuille, 1989, International Journal of Computer Vision.

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

Dong Yang, Daguang Xu, Lequan Yu, 2020, Medical Image Anal..

Efficient variational inference in large-scale Bayesian compressed sensing

George Papandreou, Alan L. Yuille, A. Yuille, 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

Mean-field phase transitions and correlation functions for Gibbs random fields

Alan L. Yuille, Ibrahim M. Elfadel, A. Yuille, 1993, Journal of Mathematical Imaging and Vision.

Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms pdf

Alan Yuille, Siyuan Qiao, Adam Kortylewski, 2021, ArXiv.

Locally Enhanced Self-Attention: Combining Self-Attention and Convolution as Local and Context Terms

Alan Yuille, Siyuan Qiao, Adam Kortylewski, 2021, 2107.05637.

Non-Rigid Point Set Registration by Preserving Global and Local Structures

Alan L. Yuille, Ji Zhao, Jiayi Ma, 2016, IEEE Transactions on Image Processing.

Probabilistic Motion Estimation Based on Temporal Coherence

Alan L. Yuille, Pierre-Yves Burgi, Norberto M. Grzywacz, 2000, Neural Computation.

Visual motion estimation and prediction: a probabilistic network model for temporal coherence

Alan L. Yuille, Pierre-Yves Burgi, Norberto M. Grzywacz, 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

Few-Shot Image Recognition by Predicting Parameters from Activations

Wei Shen, Chenxi Liu, Alan L. Yuille, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Feature Denoising for Improving Adversarial Robustness

Alan L. Yuille, Kaiming He, Laurens van der Maaten, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Exploiting Symmetry and/or Manhattan Properties for 3D Object Structure Estimation from Single and Multiple Images

Yuan Gao, Alan L. Yuille, A. Yuille, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

CHAPTER 5 SHAPE FROM SHADING, OCCLUSION AND TEXTURE

A. L. Yuille, A. Yuille, 1992 .

Statistical morphology and Bayesian reconstruction

Luc Vincent, Alan L. Yuille, Davi Geiger, 1992, Journal of Mathematical Imaging and Vision.

Shape-from-X: psychophysics and computation

Heinrich H. Buelthoff, Alan L. Yuille, A. Yuille, 1991, Other Conferences.

Statistical morphology

Alan L. Yuille, Davi Geiger, Luc M. Vincent, 1991, Optics & Photonics.

Stereo Integration, Mean Field Theory and Psychophysics

Heinrich H. Bülthoff, Alan L. Yuille, Davi Geiger, 1990, ECCV.

Self-Organizing Rules for Robust Principal Component Analysis

Lei Xu, Alan L. Yuille, A. Yuille, 1992, NIPS.

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

A. Yuille, Liang-Chieh Chen, Siyuan Qiao, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Data Fusion for Sensory Information Processing Systems

James J. Clark, Alan L. Yuille, A. Yuille, 1990 .

A common theoretical framework for visual motion's spatial and temporal coherence

A. Yuille, N. Grzywacz, A.L. Yuille, 1989, [1989] Proceedings. Workshop on Visual Motion.

Kernel regression and radial basis function net: some theoretical studies

A. Krzyzak, L. Xu, A. Yuille, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

Joint Shape Representation and Classification for Detecting PDAC

Alan L. Yuille, Yingda Xia, Elliot K. Fishman, 2018, MLMI@MICCAI.

Grouping Iso-Velocity Points for Ego-Motion Recovery

Alan L. Yuille, Yibing Yang, A. Yuille, 1992, AAAI.

AdaBoost for Text Detection in Natural Scene

Christof Koch, Alan L. Yuille, Seong-Whan Lee, 2011, 2011 International Conference on Document Analysis and Recognition.

AdaBoost for text detection

Alan Yuille, Pyoung-Hean Lee, A. Yuille, 2011 .

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose pdf

Alan Yuille, Adam Kortylewski, Angtian Wang, 2021, NeurIPS.

CRAVES: Controlling Robotic Arm With a Vision-Based Economic System

Alan L. Yuille, Weichao Qiu, Yizhou Wang, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Towards Accurate Task Accomplishment with Low-Cost Robotic Arms

Alan L. Yuille, Weichao Qiu, Yizhou Wang, 2018, 1812.00725.

Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training

Yan Wang, Wei Shen, Yuyin Zhou, 2018, 1804.02586.

Deep Co-Training for Semi-Supervised Image Recognition

Bo Wang, Alan L. Yuille, Siyuan Qiao, 2018, ECCV.

Semi-supervised multi-organ segmentation via multi-planar co-training pdf

Yan Wang, Alan L. Yuille, Yuyin Zhou, 2018, ArXiv.

Masked Feature Prediction for Self-Supervised Visual Pre-Training

A. Yuille, Saining Xie, Haoqi Fan, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

Quoc V. Le, Adams Wei Yu, Mingxing Tan, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network pdf

Adam P. Harrison, Min Sun, Alan Yuille, 2020, MICCAI.

Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification pdf

Adam P. Harrison, Alan Yuille, Jinzheng Cai, 2020, ArXiv.

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation pdf

Yan Wang, Alan L. Yuille, Qihang Yu, 2021, ArXiv.

Determining Generative Models of Objects Under Varying Illumination: Shape and Albedo from Multiple Images Using SVD and Integrability

Daniel Snow, Alan L. Yuille, Peter N. Belhumeur, 1999, International Journal of Computer Vision.

Image Warping for Shape Recovery and Recognition

Alan L. Yuille, Mario Ferraro, Tony Zhang, 1998, Comput. Vis. Image Underst..

Shape and albedo from multiple images using integrability

Daniel Snow, Alan L. Yuille, A. Yuille, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Surface shape from warping

Alan L. Yuille, Mario Ferraro, Tony Zhang, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Adversarial Examples Improve Image Recognition

Quoc V. Le, Cihang Xie, Mingxing Tan, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Organ at Risk Segmentation for Head and Neck Cancer Using Stratified Learning and Neural Architecture Search

Adam P. Harrison, Alan Yuille, Dakai Jin, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

External Attention Assisted Multi-Phase Splenic Vascular Injury Segmentation With Limited Data

Yan Wang, Yuyin Zhou, David Dreizin, 2021, IEEE Transactions on Medical Imaging.

Added value of deep learning-based liver parenchymal CT volumetry for predicting major arterial injury after blunt hepatic trauma: a decision tree analysis

A. Yuille, Yan Wang, D. Dreizin, 2021, Abdominal Radiology.

A Multiscale Deep Learning Method for Quantitative Visualization of Traumatic Hemoperitoneum at CT: Assessment of Feasibility and Comparison with Subjective Categorical Estimation.

Guang Li, Yan Wang, Yuyin Zhou, 2020, Radiology. Artificial intelligence.

Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures

Yan Wang, Yingwei Li, Yuyin Zhou, 2019, MLMI@MICCAI.

CT Radiomics-Based Preoperative Survival Prediction in Patients With Pancreatic Ductal Adenocarcinoma.

A. Yuille, Seyoun Park, L. Chu, 2021, AJR. American journal of roentgenology.

Classification of spatially unaligned fMRI scans

Alan L. Yuille, Ivo D. Dinov, Mark S. Cohen, 2010, NeuroImage.

Semi-Supervised 3D Abdominal Multi-Organ Segmentation Via Deep Multi-Planar Co-Training

Wei Shen, Song Bai, Alan L. Yuille, 2018, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles

A. Yuille, Weichao Qiu, Adam Kortylewski, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Joint Multi-person Pose Estimation and Semantic Part Segmentation

Peng Wang, Alan L. Yuille, Xianjie Chen, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Pose-Guided Human Parsing by an AND/OR Graph Using Pose-Context Features

Jun Zhu, Alan L. Yuille, Peng Wang, 2016, AAAI.

Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net

Alan L. Yuille, Liang-Chieh Chen, Peng Wang, 2015, ECCV.

Joint Object and Part Segmentation Using Deep Learned Potentials

Alan L. Yuille, Zhe L. Lin, Scott Cohen, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Semantic part segmentation using compositional model combining shape and appearance

Alan L. Yuille, Jianyu Wang, A. Yuille, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency pdf

Alan L. Yuille, Xiaochen Lian, Wenhao Lu, 2014, BMVC.

Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts

Sanja Fidler, Roozbeh Mottaghi, Alan L. Yuille, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2008, ECCV.

Bayesian A* Tree Search with Expected O(N) Convergence Rates for Road Tracking

Alan L. Yuille, James M. Coughlan, A. Yuille, 1999, EMMCVPR.

A statistical approach to multi-scale edge detection

Alan L. Yuille, James M. Coughlan, Scott Konishi, 2003, Image Vis. Comput..

Multilevel Enhancement and Detection of Stereo Disparity Surfaces

Alan L. Yuille, Yibing Yang, A. Yuille, 1995, Artif. Intell..

Quadrature and the development of orientation selective cortical cells by Hebb rules

D. M. Kammen, A. L. Yuille, D. S. Cohen, 1989, Biological Cybernetics.

A Model for the Estimate of Local Velocity

Alan L. Yuille, Norberto M. Grzywacz, A. Yuille, 1990, ECCV.

Recent Advances on Techniques of Static Feedforward Networks with Supervised Learning

Lei Xu, Alan L. Yuille, Stan Klasa, 1992, Int. J. Neural Syst..

Occluded Video Instance Segmentation pdf

Song Bai, Xiang Bai, Jiyang Qi, 2021, ArXiv.

NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction

Wei Liu, Yuan Gao, Alan L. Yuille, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

An information theory perspective on computational vision

Alan L. Yuille, A. Yuille, 2010 .

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

Alan L. Yuille, Hongjing Lu, Tom Beckers, 2016, Cogn. Sci..

Some perspective projection invariants

Alan L. Yuille, Alessandro Verri, A. Verri, 1988 .

Complexity of Representation and Inference in Compositional Models with Part Sharing

Roozbeh Mottaghi, Alan L. Yuille, A. Yuille, 2013, J. Mach. Learn. Res..

Recursive Compositional Models for Vision: Description and Review of Recent Work

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2011, Journal of Mathematical Imaging and Vision.

Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Learning a Hierarchical Log-Linear Model for Rapid Deformable Object Parsing

Long Zhu, Alan Yuille, Yuanhao Chen, 2008 .

Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses pdf

Song Bai, Yingwei Li, Alan L. Yuille, 2019, ECCV.

iBOT: Image BERT Pre-Training with Online Tokenizer pdf

Tao Kong, Jinghao Zhou, Alan Yuille, 2021, ArXiv.

Are Transformers More Robust Than CNNs? pdf

Alan Yuille, Jieru Mei, Cihang Xie, 2021, NeurIPS.

Determining The Optimal Weights In Multiple Objective Function Optimization

Alan L. Yuille, Michael A. Gennert, A. Yuille, 1988, [1988 Proceedings] Second International Conference on Computer Vision.

CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning

A. Yuille, Kihyuk Sohn, Fan Yang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval

Qing Liu, Alan L. Yuille, Lingxi Xie, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

A Generative Model Based Approach to Motion Segmentation

Daniel Cremers, Alan L. Yuille, A. Yuille, 2003, DAGM-Symposium.

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions

A. Yuille, R. Scharpf, L. Wood, 2023, bioRxiv.

A Bayesian network framework for relational shape matching

Alan L. Yuille, James M. Coughlan, Anand Rangarajan, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

Diffusion Models as Masked Autoencoders

Cihang Xie, A. Yuille, Haoqi Fan, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

CLEVR-Ref+: Diagnosing Visual Reasoning With Referring Expressions

Chenxi Liu, Alan L. Yuille, Runtao Liu, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution pdf

Hong Chen, Alan L. Yuille, Hao Lu, 2018, EMNLP.

Intriguing properties of adversarial training pdf

Alan Yuille, Cihang Xie, Cihang Xie, 2019, ICLR.

An A* perspective on deterministic optimization for deformable templates

Alan L. Yuille, James M. Coughlan, A. Yuille, 2000, Pattern Recognit..

InterActive: Inter-Layer Activeness Propagation

Qi Tian, Jingdong Wang, Alan L. Yuille, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Parsing occluded people by flexible compositions

Alan L. Yuille, Xianjie Chen, A. Yuille, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations

Alan L. Yuille, Xianjie Chen, A. Yuille, 2014, NIPS.

Special Issue: Probabilistic models of cognition Probabilistic models of cognition: Conceptual foundations

J. Tenenbaum, A. Yuille, N. Chater, 2006 .

Context-Aware Group Captioning via Self-Attention and Contrastive Features

Quan Hung Tran, Quan Tran, Zhe L. Lin, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

MAT: A Multimodal Attentive Translator for Image Captioning pdf

Fuchun Sun, Changhu Wang, Chang Liu, 2017, IJCAI.

Label-Free Liver Tumor Segmentation

A. Yuille, Junfei Xiao, Shuwen Sun, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Large sample group independent component analysis of functional magnetic resonance imaging using anatomical atlas‐based reduction and bootstrapped clustering

Alan L. Yuille, Mark S. Cohen, Agatha Lenartowicz, 2011, Int. J. Imaging Syst. Technol..

Image BERT Pre-training with Online Tokenizer

Cihang Xie, A. Yuille, Wei Shen, 2022, ICLR.

ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation pdf

Cewu Lu, Gongshen Liu, Alan Yuille, 2020, BMVC.

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

Li Fei-Fei, Chenxi Liu, Wei Hua, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Vision: Bayesian Inference and Beyond

A. Yuille, D. Kersten, 2014 .

Prior-Aware Neural Network for Partially-Supervised Multi-Organ Segmentation

Xinlei Chen, Mei Han, Chong Wang, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Abdominal multi-organ segmentation with organ-attention networks and statistical fusion

Yan Wang, Alan L. Yuille, Yuyin Zhou, 2018, Medical Image Anal..

Automated MR image processing and analysis of malignant brain tumors: enabling technology for data mining

Alan L. Yuille, Usha Sinha, Jason J. Corso, 2007 .

Signfinder: using color to detect, localize and identify informational signs

Daniel Snow, Alan L. Yuille, Mark Nitzberg, 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

Rethinking Normalization and Elimination Singularity in Neural Networks pdf

Chenxi Liu, Wei Shen, Alan Yuille, 2019, ArXiv.

SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering

A. Yuille, Vipul Gupta, Yingwei Li, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

A. Yuille, C. Theobalt, O. Zendel, 2023, ArXiv.

Probabilistic models of vision and max-margin methods

Alan L. Yuille, Xuming He, A. Yuille, 2012 .

HOP: Hierarchical object parsing

Iasonas Kokkinos, Alan L. Yuille, A. Yuille, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Recursive Segmentation and Recognition Templates for 2D Parsing

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2008, NIPS.

Shape matching and registration by data-driven EM

Zhuowen Tu, Alan L. Yuille, Songfeng Zheng, 2008, Comput. Vis. Image Underst..

Automated Extraction of the Cortical Sulci Based on a Supervised Learning Approach

Paul M. Thompson, Arthur W. Toga, Zhuowen Tu, 2007, IEEE Transactions on Medical Imaging.

A Hierarchical Compositional System for Rapid Object Detection

Long Zhu, Alan L. Yuille, A. Yuille, 2005, NIPS.

Detecting and reading text in natural scenes

Alan L. Yuille, Xiangrong Chen, A. Yuille, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Snapshot Distillation: Teacher-Student Optimization in One Generation

Alan L. Yuille, Chi Su, Lingxi Xie, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief

Alan L. Yuille, Mark S. Cohen, Pamela K. Douglas, 2011, NeuroImage.

PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning

Cihang Xie, A. Yuille, Yinzhi Cao, 2020, ECCV.

Multi-context Attention for Human Pose Estimation

Xiaogang Wang, Cheng Ma, Wei Yang, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Mean-field theory for grayscale texture synthesis using Gibbs random fields

Ibrahim M. Elfadel, Alan L. Yuille, A. Yuille, 1991, Optics & Photonics.

Unsupervised Learning of Object Deformation Models

Iasonas Kokkinos, Alan L. Yuille, A. Yuille, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students

Alan L. Yuille, Siyuan Qiao, Lingxi Xie, 2018, AAAI.

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans

Yan Wang, Alan L. Yuille, Qihang Yu, 2020, IEEE Transactions on Medical Imaging.

V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation

Daguang Xu, Chenxi Liu, Dong Yang, 2019, 2019 International Conference on 3D Vision (3DV).

A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

Alan L. Yuille, Yingda Xia, Elliot K. Fishman, 2017, 2018 International Conference on 3D Vision (3DV).

Bayesian models of object perception

Daniel Kersten, Alan Yuille, A. Yuille, 2003, Current Opinion in Neurobiology.

Current Status of Radiomics and Deep Learning in Liver Imaging

A. Yuille, Seyoun Park, L. Chu, 2021, Journal of computer assisted tomography.

Symmetric Non-rigid Structure from Motion for Category-Specific Object Structure Estimation

Yuan Gao, Alan L. Yuille, A. Yuille, 2016, ECCV.

A Light-weight Interpretable CompositionalNetwork for Nuclei Detection and Weakly-supervised Segmentation pdf

Alan Yuille, Adam Kortylewski, Qing Liu, 2021, ArXiv.

SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data pdf

Yi Zhang, Alan L. Yuille, Weichao Qiu, 2018, BMVC.

Improving Transferability of Adversarial Examples With Input Diversity

Alan L. Yuille, Yuyin Zhou, Zhishuai Zhang, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Searching for TrioNet: Combining Convolution with Local and Global Self-Attention pdf

Alan Yuille, Huiyu Wang, Huaijin Pi, 2021, BMVC.

A framework for shape representation and recognition

Alan L. Yuille, Song-Chun Zhu, A. Yuille, 1994, Proceedings of 1st International Conference on Image Processing.

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

A. Yuille, Yixuan Yuan, Yongyi Lu, 2023, ArXiv.

In-painting Radiography Images for Unsupervised Anomaly Detection

A. Yuille, Weidong (Tom) Cai, Yongyi Lu, 2021, ArXiv.

A Light-Weight Interpretable Model for Nuclei Detection and Weakly-Supervised Segmentation

A. Yuille, Seyoun Park, J. Taube, 2022, MOVI@MICCAI.

Bayesian Self-Organization Driven by Prior Probability Distributions

Lei Xu, Alan L. Yuille, Stelios M. Smirnakis, 1995, Neural Computation.

Bayesian Self-Organization

Lei Xu, Alan L. Yuille, Stelios M. Smirnakis, 1993, NIPS.

Deep Regression Forests for Age Estimation

Bo Wang, Yan Wang, Kai Zhao, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

When Radiology Report Generation Meets Knowledge Graph pdf

Daguang Xu, Xiaosong Wang, Qihang Yu, 2020, AAAI.

The Secrets of Salient Object Segmentation

James M. Rehg, Yin Li, Christof Koch, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Point-Level Region Contrast for Object Detection Pre-Training

A. Berg, A. Yuille, Xinlei Chen, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

PartImageNet: A Large, High-Quality Dataset of Parts

A. Yuille, Ju He, Shuo Yang, 2021, ECCV.

MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models

A. Yuille, Liang-Chieh Chen, Hartwig Adam, 2022, ICLR.

k-means Mask Transformer

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022, ECCV.

Robust Object Detection Under Occlusion With Context-Aware CompositionalNets

Alan Yuille, Adam Kortylewski, Yihong Sun, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

NormFace: L2 Hypersphere Embedding for Face Verification

Jian Cheng, Xiang Xiang, Feng Wang, 2017, ACM Multimedia.

Grouped Spatial-Temporal Aggregation for Efficient Action Recognition

Alan Yuille, Chenxu Luo, A. Yuille, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

Wenyu Liu, Song Bai, Xiang Bai, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Annotating 8, 000 Abdominal CT Volumes for Multi-Organ Segmentation in Three Weeks

A. Yuille, Zongwei Zhou, Yucheng Tang, 2023, ArXiv.

Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation pdf

Yan Wang, Wei Shen, Yuyin Zhou, 2020, MICCAI.

Iterative Reorganization With Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning

Qi Tian, Chen Wei, Alan L. Yuille, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

TransFG: A Transformer Architecture for Fine-grained Recognition pdf

Alan Yuille, Adam Kortylewski, Changhu Wang, 2021, AAAI.

COMPAS: Representation Learning with Compositional Part Sharing for Few-Shot Classification

A. Yuille, Ju He, Adam Kortylewski, 2021, ArXiv.

CGPart: A Part Segmentation Dataset Based on 3D Computer Graphics Models pdf

Weichao Qiu, Alan Yuille, Adam Kortylewski, 2021, ArXiv.

Unsupervised learning of object semantic parts from internal states of CNNs by population encoding

Alan Yuille, Zhishuai Zhang, Jianyu Wang, 2015, 1511.06855.

Lite Vision Transformer with Enhanced Self-Attention pdf

Zhe L. Lin, Alan Yuille, Zijun Wei, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

DeepLab2: A TensorFlow Library for Deep Labeling pdf

Daniel Cremers, Alan L. Yuille, Qihang Yu, 2021, ArXiv.

Glance-and-Gaze Vision Transformer pdf

Yingda Xia, Qihang Yu, Alan Yuille, 2021, NeurIPS.

Understanding Catastrophic Forgetting and Remembering in Continual Learning with Optimal Relevance Mapping pdf

Alan Yuille, Adam Kortylewski, Alex Gain, 2021, ArXiv.

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques pdf

Yan Wang, Dawn Song, Dacheng Tao, 2021, ArXiv.

Adversarial Attacks and Defences Competition pdf

Yao Zhao, Takuya Akiba, Motoki Abe, 2018, ArXiv.

InstMove: Instance Motion for Object-centric Video Segmentation

A. Yuille, S. Bai, Xiang Bai, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Self-Supervised Pillar Motion Learning for Autonomous Driving

Alan Yuille, Xiaodong Yang, Chenxu Luo, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Every View Counts: Cross-View Consistency in 3D Object Detection with Hybrid-Cylindrical-Spherical Voxelization

Alan L. Yuille, Lin Sun, Qi Chen, 2020, NeurIPS.

Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding

Wei Xu, Ramakant Nevatia, Zhenheng Yang, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

AsyInst: Asymmetric Affinity with DepthGrad and Color for Box-Supervised Instance Segmentation

A. Yuille, Hang Zhao, Junfei Xiao, 2022, ArXiv.

Universal Physical Camouflage Attacks on Object Detectors

Cihang Xie, A. Yuille, Yuyin Zhou, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles pdf

Alan Yuille, Lin Sun, Chenxu Luo, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Robust Instance Segmentation through Reasoning about Multi-Object Occlusion pdf

Alan Yuille, Adam Kortylewski, Xiaoding Yuan, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Rethinking Monocular Depth Estimation with Adversarial Training pdf

Alan L. Yuille, Richard J. Chen, Faisal Mahmood, 2018, ArXiv.

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving pdf

Alan Yuille, Xiaodong Yang, Chenxu Luo, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Deeply Shape-guided Cascade for Instance Segmentation

Alan Yuille, Siyuan Qiao, Wei Shen, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Robust $L_{2}E$ Estimation of Transformation for Non-Rigid Registration

Zhuowen Tu, Alan L. Yuille, Weichao Qiu, 2015, IEEE Transactions on Signal Processing.

Single-Shot Object Detection with Enriched Semantics

Bo Wang, Alan L. Yuille, Siyuan Qiao, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Mask Guided Matting via Progressive Refinement Network pdf

Ning Xu, Qihang Yu, Zhe L. Lin, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

DASZL: Dynamic Action Signatures for Zero-shot Learning

Gregory D. Hager, Michael Peven, Zihao Xiao, 2019, AAAI.

Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans

A. Yuille, Jingren Zhou, Le Lu, 2023, ArXiv.

The FELIX Project: Deep Networks To Detect Pancreatic Neoplasms

A. Yuille, B. Vogelstein, R. Hruban, 2022, medRxiv.

Label-Assemble: Leveraging Multiple Datasets with Partial Labels

A. Yuille, Yongyi Lu, Zongwei Zhou, 2021, 2109.12265.

Recurrent Multimodal Interaction for Referring Image Segmentation

Chenxi Liu, Alan L. Yuille, Zhe L. Lin, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition Under Occlusion pdf

Alan Yuille, Adam Kortylewski, Qing Liu, 2020, International Journal of Computer Vision.

Object Recognition with and without Objects

Alan L. Yuille, Lingxi Xie, Zhuotun Zhu, 2016, IJCAI.

AtomNAS: Fine-Grained End-to-End Neural Architecture Search

A. Yuille, Jianchao Yang, Xiaojie Jin, 2019, ICLR.

Nothing But Geometric Constraints: A Model-Free Method for Articulated Object Pose Estimation pdf

Gregory D. Hager, Alan L. Yuille, Weichao Qiu, 2020, ArXiv.

Visual analogy: Deep learning versus compositional models pdf

Alan Yuille, Keith J. Holyoak, Nicholas Ichien, 2021, ArXiv.

Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation pdf

Yingda Xia, Wei Shen, Alan Yuille, 2020, ECCV.

Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints From Limited Training Data

Qing Liu, Yan Zheng, Alan L. Yuille, 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection Under Partial Occlusion

Alan L. Yuille, Zhishuai Zhang, Jianyu Wang, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Attention Correctness in Neural Image Captioning pdf

Chenxi Liu, Alan L. Yuille, Fei Sha, 2016, AAAI.

Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm

Jun Zhu, Alan L. Yuille, Junhua Mao, 2014, NIPS.

NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation pdf

Alan Yuille, Adam Kortylewski, Angtian Wang, 2021, ICLR.

Identifying Model Weakness with Adversarial Examiner pdf

Chenxi Liu, Weichao Qiu, Alan Yuille, 2019, AAAI.

TransMix: Attend to Mix for Vision Transformers pdf

Song Bai, Alan Yuille, Philip H. S. Torr, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

OriNet: A Fully Convolutional Network for 3D Human Pose Estimation pdf

Alan L. Yuille, Xiao Chu, Chenxu Luo, 2018, BMVC.

Learning From Synthetic Animals

A. Yuille, Gregory Hager, Weichao Qiu, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections

Ehsan Jahangiri, Alan L. Yuille, A. Yuille, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

Learning Road Scene-level Representations via Semantic Region Prediction

A. Yuille, Zihao Xiao, Yi-Ting Chen, 2023, CoRL.

A Time-Efficient Cascade for Real-Time Object Detection: With applications for the visually impaired

Alan L. Yuille, Xiangrong Chen, A. Yuille, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

Yan Wang, Alan L. Yuille, Yuyin Zhou, 2016, MICCAI.

Detecting Pancreatic Ductal Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble

A. Yuille, E. Fishman, Yuyin Zhou, 2020, MICCAI.

MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification pdf

Alan Yuille, Yongyi Lu, Bin Li, 2021, ArXiv.

Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency

Zhenheng Yang, Alan Yuille, Vignesh Ramanathan, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference

Alan L. Yuille, James M. Coughlan, A. Yuille, 2000, NIPS.

Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge pdf

Song Bai, Jiyang Qi, Xinggang Wang, 2021, NeurIPS Datasets and Benchmarks.

CO2: Consistent Contrast for Unsupervised Visual Representation Learning pdf

Wei Shen, Alan Yuille, Chen Wei, 2020, ICLR.

Semi-Supervised Sparse Representation Based Classification for Face Recognition With Insufficient Labeled Samples

Alan L. Yuille, Yuan Gao, Jiayi Ma, 2016, IEEE Transactions on Image Processing.

Robust Estimation of Nonrigid Transformation for Point Set Registration

Zhuowen Tu, Alan L. Yuille, Ji Zhao, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Occlusions and binocular stereo

Alan L. Yuille, Davi Geiger, Bruce Ladendorf, 1992, International Journal of Computer Vision.

Bayesian models, deformable templates and competitive priors

James J. Clark, Allan L. Yuille, A. Yuille, 1994 .

A Primer on Probabilistic Inference

Thomas L. Griffiths, Alan L. Yuille, A. Yuille, 2008 .

Compositional Generative Networks and Robustness to Perceptible Image Changes

Alan L. Yuille, Adam Kortylewski, Christian Cosgrove, 2021, 2021 55th Annual Conference on Information Sciences and Systems (CISS).

Compositional Convolutional Neural Networks: A Deep Architecture With Innate Robustness to Partial Occlusion

Qing Liu, Alan Yuille, Adam Kortylewski, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Spatiotemporal information storage in a content addressable memory using realistic neurons

Alan L. Yuille, Masakazu Matsugu, A. Yuille, 1994, Neural Networks.

Pancreatic Cancer Imaging: A New Look at an Old Problem.

Elliot K Fishman, Satomi Kawamoto, Alan L Yuille, 2020, Current problems in diagnostic radiology.

Scene Graph Parsing as Dependency Parsing pdf

Chenxi Liu, Alan L. Yuille, Xiaohui Zeng, 2018, NAACL.

Visual Concepts and Compositional Voting pdf

Jun Zhu, Alan L. Yuille, Yuyin Zhou, 2017, ArXiv.

Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help?

Alan L. Yuille, Song-Chun Zhu, Ying Nian Wu, 2004, International Journal of Computer Vision.

Unsupervised Learning Using Generative Adversarial Training And Clustering

Alan L. Yuille, Vittal Premachandran, A. Yuille, 2016 .

A Novel Linelet-Based Representation for Line Segment Detection

Alan Yuille, Seong-Whan Lee, Nam-Gyu Cho, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Pancreas Segmentation in Abdominal CT Scan: A Coarse-to-Fine Approach pdf

Alan L. Yuille, Yuyin Zhou, Elliot K. Fishman, 2016, ArXiv.

Robust Face Detection via Learning Small Faces on Hard Images

Yan Wang, Bo Wang, Wei Shen, 2018, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

DOC: Deep OCclusion Estimation from a Single Image

Alan L. Yuille, Peng Wang, A. Yuille, 2015, ECCV.

DOC: Deep OCclusion Recovering From A Single Image pdf

Alan L. Yuille, Peng Wang, A. Yuille, 2015, ArXiv.

Benchmarking Robustness in Neural Radiance Fields

Cihang Xie, A. Yuille, Angtian Wang, 2023, ArXiv.

Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD

Alan L. Yuille, Ying Nian Wu, Mark S. Cohen, 2014, NeuroImage.

High-level and generic models for visual search: When does high level knowledge help?

Alan L. Yuille, James M. Coughlan, A. Yuille, 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

Single Image Super-resolution Using Deformable Patches

Yanning Zhang, Alan L. Yuille, Yu Zhu, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Adversarial Examples for Edge Detection: They Exist, and They Transfer

Alan L. Yuille, Christian Cosgrove, A. Yuille, 2019, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation pdf

Daguang Xu, Baris Turkbey, Holger Roth, 2021, ArXiv.

Compositor: Bottom-Up Clustering and Compositing for Robust Part and Object Segmentation

Qihang Yu, A. Yuille, Qihang Yu, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Modeling Causal Learning Using Bayesian Generic Priors on Generative and Preventive Powers

Alan L. Yuille, Keith J. Holyoak, Hongjing Lu, 2011 .

Deep Differentiable Random Forests for Age Estimation

Yan Wang, Alan L. Yuille, Wei Shen, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A computational theory for the perception of coherent motion: From ideal observer to generic models

Hongjing Lu, Alan L. Yuille, A. Yuille, 2010 .

Human and Ideal Observers for Detecting Image Curves

Paul R. Schrater, Alan L. Yuille, Fang Fang, 2003, NIPS.

Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning pdf

Alan Yuille, Adam Kortylewski, Changhu Wang, 2021, ArXiv.

Zero-shot Recognition of Complex Action Sequences pdf

Gregory D. Hager, Michael Peven, Jonathan D. Jones, 2019, ArXiv.

Training a general purpose deformable template

Alan L. Yuille, Russell Epstein, A. Yuille, 1994, Proceedings of 1st International Conference on Image Processing.

Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images

Alan L. Yuille, Yushi Jing, Junhua Mao, 2016, NIPS.

Adaptive occlusion state estimation for human pose tracking under self-occlusions

Alan L. Yuille, Seong-Whan Lee, Nam-Gyu Cho, 2013, Pattern Recognit..

TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

A. Yuille, Wei Shen, Siyuan Qiao, 2019, ECCV Workshops.

Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion

Zhishuai Zhang, A. Yuille, Huiyu Wang, 2019, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models

Alan L. Yuille, Hongru Zhu, Peng Tang, 2019, CogSci.

The Smoothest Velocity Field and Token Matching

Alan L. Yuille, A. Yuille, 1983 .

Segmentation of Sub-cortical Structures by the Graph-Shifts Algorithm

Arthur W. Toga, Zhuowen Tu, Alan L. Yuille, 2007, IPMI.

Bottom-Up & Top-down Object Detection using Primal Sketch Features and Graphical Models

Iasonas Kokkinos, Petros Maragos, Alan L. Yuille, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

ELASTIC: Improving CNNs With Dynamic Scaling Policies

Ali Farhadi, Alan Yuille, Mohammad Rastegari, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Weakly Supervised Region Proposal Network and Object Detection

Wenyu Liu, Alan L. Yuille, Xinggang Wang, 2018, ECCV.

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

A. Yuille, Yixuan Yuan, Yongyi Lu, 2023, ArXiv.

Unleashing the Power of Visual Prompting At the Pixel Level

Cihang Xie, A. Yuille, Yuyin Zhou, 2022, ArXiv.

Track finding with deformable templates

Carsten Peterson, Alan L. Yuille, Mattias Ohlsson, 1991 .

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

Youbao Tang, Alan L. Yuille, Jing Xiao, 2021, MICCAI.

Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans

Alan L. Yuille, Yuyin Zhou, Elliot K. Fishman, 2017, MICCAI.

Empirical Minimum Bayes Risk Prediction

Alan L. Yuille, Daniel Tarlow, Dhruv Batra, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Shape Reconstructability Measure of Object Part Importance with Applications to Object Detection and Localization

Wen Gao, Alan L. Yuille, Fang Fang, 2014, International Journal of Computer Vision.

Computing importance of 2D contour parts by reconstructability

Wen Gao, Alan L. Yuille, Ge Guo, 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection

A. Yuille, Weidong (Tom) Cai, Yongyi Lu, 2021, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Weight Standardization pdf

Wei Shen, Chenxi Liu, Alan L. Yuille, 2019, ArXiv.

Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2007, NIPS.

Making Your First Choice: To Address Cold Start Problem in Medical Active Learning

A. Yuille, Zongwei Zhou, Liangyu Chen, 2023, MIDL.

Adding 3D Geometry Control to Diffusion Models

A. Yuille, Angtian Wang, Yaoyao Liu, 2023, ArXiv.

Can Temporal Information Help with Contrastive Self-Supervised Learning? pdf

Qihang Yu, Yuyin Zhou, Alan Yuille, 2020, ArXiv.

I BOT : I MAGE BERT P RE -T RAINING WITH O NLINE T OKENIZER

Cihang Xie, A. Yuille, Huiyu Wang, 2022 .

CO 2 : C ONSISTENT C ONTRAST FOR U NSUPERVISED V ISUAL R EPRESENTATION L EARNING

A. Yuille, Wei Shen, Huiyu Wang, 2021 .

Batch Normalization with Enhanced Linear Transformation pdf

Alan Yuille, Siyuan Qiao, Hongkai Xiong, 2020, ArXiv.

F AST A DV P ROP

Cihang Xie, A. Yuille, Yingwei Li, 2022 .

Max Margin Learning of Hierarchical Configural Deformable Templates (HCDTs) for Efficient Object Parsing and Pose Estimation

Long Zhu, Yuanhao Chen, Alan L. Yuille, 2011, International Journal of Computer Vision.

Learning Transferable Adversarial Examples via Ghost Networks

Song Bai, Yingwei Li, Alan L. Yuille, 2018, AAAI.

Sobolev gradients and joint variational image segmentation, denoising, and deblurring

Alan L. Yuille, Ganesh Sundaramoorthi, Luminita A. Vese, 2009, Electronic Imaging.

Elastic Boundary Projection for 3D Medical Image Segmentation

Tianwei Ni, Alan L. Yuille, Elliot K. Fishman, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Structured Prediction using cGANs with Fusion Discriminator pdf

Alan L. Yuille, Faisal Mahmood, Nicholas J. Durr, 2019, DGS@ICLR.

Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation

A. Yuille, Liang-Chieh Chen, G. Papandreou, 2015, ArXiv.

Graph-shifts: Natural image labeling by dynamic hierarchical computing

Zhuowen Tu, Alan L. Yuille, Jason J. Corso, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

An Active Patch Model for Real World Texture and Appearance Classification

Jun Zhu, Alan L. Yuille, Junhua Mao, 2014, ECCV.

STFlow: Self-Taught Optical Flow Estimation Using Pseudo Labels

Wenhan Luo, Hongyuan Zha, Zhe Ren, 2020, IEEE Transactions on Image Processing.

Unsupervised learning of optical flow with patch consistency and occlusion estimation

Hongyuan Zha, Zhe Ren, Junchi Yan, 2020, Pattern Recognit..

Multiple Instance Visual-Semantic Embedding

Alan L. Yuille, Hailin Jin, Zhe L. Lin, 2017 .

A unified model of short-range and long-range motion perception

Shuang Wu, Alan L. Yuille, Xuming He, 2010, NIPS.

Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks

A. Yuille, Zongwei Zhou, Yixiong Chen, 2023, ICLR.

Representing Data by a Mixture of Activated Simplices pdf

John Flynn, Alan L. Yuille, Chunyu Wang, 2014, ArXiv.

WEOTAWEO 2 LSTM WEO 1 Encoding WSS 1 WSS 2 WSSTB Decoding Attention Cell

A. Yuille, F. Sun, Changhu Wang, 2018 .

Assembling Existing Labels from Public Datasets to Diagnose Novel Diseases: COVID-19 in Late 2019

A. Yuille, Zongwei Zhou, Mintong Kang, 2022 .

Data-Assemble: Leveraging Multiple Datasets with Partial Labels

Alan L. Yuille, Yongyi Lu, Zongwei Zhou, 2021 .

Shape-aware Feature Extraction for Instance Segmentation pdf

Wei Shen, Alan Yuille, Siyuan Qiao, 2019, ArXiv.

Mining 3D Key-Pose-Motifs for Action Recognition

Alan L. Yuille, Yizhou Wang, Chun-yu Wang, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Joint Image-Text Representation by Gaussian Visual-Semantic Embedding

Alan L. Yuille, Hailin Jin, Zhe L. Lin, 2016, ACM Multimedia.

Multi-Instance Visual-Semantic Embedding pdf

Alan L. Yuille, Hailin Jin, Zhe L. Lin, 2015, BMVC 2017.

k-means Mask Transformer

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022, ECCV.

kMaX-DeepLab: k-means Mask Transformer

Maxwell D. Collins, A. Yuille, Liang-Chieh Chen, 2022, 2207.04044.

ATTENTION BRINGS STRONG VISION MODELS

A. Yuille, Liang-Chieh Chen, Hartwig Adam, 2023 .

UnrealStereo: A Synthetic Dataset for Analyzing Stereo Vision pdf

Xiaolin Hu, Yi Zhang, Alan L. Yuille, 2016, ArXiv.

VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis

A. Yuille, Jian Sun, Angtian Wang, 2022, ICLR.

Label Distribution Learning Forests

Kai Zhao, Alan L. Yuille, Wei Shen, 2017, NIPS.

Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images pdf

Benjamin Van Durme, Alan Yuille, Zhuowan Li, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization

Alan L. Yuille, Jianming Zhang, Zhe L. Lin, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Weakly-Supervised Amodal Instance Segmentation with Compositional Priors

A. Yuille, Adam Kortylewski, Yihong Sun, 2020, ArXiv.

Fidelity-Naturalness Evaluation of Single Image Super Resolution pdf

Alan L. Yuille, Yu Zhu, Lingxi Xie, 2015, ArXiv.

Modeling deformable gradient compositions for single-image super-resolution

Yanning Zhang, Alan L. Yuille, Yu Zhu, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

A. Yuille, Yixuan Yuan, Yongyi Lu, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

A depth recovery algorithm using defocus information

Alan L. Yuille, James J. Clark, Ten-lee Hwang, 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Transferring Face Verification Nets To Pain and Expression Regression pdf

Gregory D. Hager, Austin Reiter, Trac D. Tran, 2017, ArXiv.

A Computational Model of Jazz Improvisation Inspired by Language

Alan L. Yuille, Cody Komers, A. Yuille, 2015, CogSci.

Controlling Robotic Arm with a Vision-based Economic System Supplementary Materials

A. Yuille, Yizhou Wang, Lingxi Xie, 2019 .

PASCAL Boundaries: A Semantic Boundary Dataset with a Deep Semantic Boundary Detector

Alan L. Yuille, Vittal Premachandran, Boyan Bonev, 2017, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).

PASCAL Boundaries: A Class-Agnostic Semantic Boundary Dataset pdf

Alan L. Yuille, Vittal Premachandran, Boyan Bonev, 2015, ArXiv.

Learning a Dictionary of Shape Epitomes with Applications to Image Labeling

George Papandreou, Alan L. Yuille, Liang-Chieh Chen, 2013, 2013 IEEE International Conference on Computer Vision.

A Meta-Theory of Boundary Detection Benchmarks pdf

Christof Koch, Alan L. Yuille, Xiaodi Hou, 2013, ArXiv.

Occlusion Boundary Detection Using Pseudo-depth

Alan L. Yuille, Xuming He, A. Yuille, 2010, ECCV.

Detecting Object Boundaries Using Low-, Mid-, and High-level Information

A. Yuille, Z. Tu, Songfeng Zheng, 2007, CVPR.

3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training

Dong Yang, Daguang Xu, Holger Roth, 2018, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

Regularizing face verification nets for pain intensity regression

Gregory D. Hager, Austin Reiter, Trac D. Tran, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Deep Collaborative Learning for Visual Recognition pdf

Yan Wang, Ya Zhang, Wenjun Zhang, 2017, ArXiv.

Modeling Image Patches with a Generic Dictionary of Mini-epitomes

George Papandreou, Alan L. Yuille, Liang-Chieh Chen, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Non-Rigid Motion and Regge Calculus.

Alan L. Yuille, Rado Jasinschi, A. Yuille, 1989 .

NDDR-CNN: Layer-wise Feature Fusing in Multi-Task CNN by Neural Discriminative Dimensionality Reduction

A. Yuille, Jiayi Ma, Mingde Zhao, 2018, ArXiv.

Guest Editorial: Statistical and Computational Theories of Vision: Modeling, Learning, Sampling and Computing, Part I

Alan L. Yuille, Song-Chun Zhu, David Mumford, 2000, International Journal of Computer Vision.

Robust L2E Estimation of Transformation for Non-Rigid Registration

A. Yuille, Z. Tu, Weichao Qiu, 2015, IEEE Trans. Signal Process..

Robust Category-Level 3D Pose Estimation from Synthetic Data

A. Yuille, Angtian Wang, Adam Kortylewski, 2023, 2305.16124.

Identity Preserve Transform: Understand What Activity Classification Models Have Learnt

Weichao Qiu, Alan Yuille, Yi Zhang, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

CateNorm: Categorical Normalization for Robust Medical Image Segmentation

A. Yuille, Yuyin Zhou, Yutong Bai, 2021, DART@MICCAI.

Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction

Yan Wang, Yuyin Zhou, Wei Shen, 2021, IEEE Transactions on Medical Imaging.

A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

A. Yuille, E. Fishman, Zhuotun Zhu, 2017, 2018 International Conference on 3D Vision (3DV).

3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation

A. Yuille, Yi Zhang, Jieru Mei, 2023, ArXiv.

Sequential causal learning in humans and rats

Alan L. Yuille, Tom Beckers, Randall R. Rojas, 2008 .

Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training

A. Yuille, E. Fishman, S. Bai, 2018 .

Seeing the Meaning: Vision Meets Semantics in Solving Pictorial Analogy Problems

Alan L. Yuille, Hongjing Lu, Keith J. Holyoak, 2019, CogSci.

Supplementary Material for the Paper: Symmetric Non-Rigid Structure from Motion for Category-Specific Object Structure Estimation

A. Yuille, Yuan Gao, 2016 .

Max Margin AND/OR Graph learning for parsing the human body

Yifei Lu, Long Zhu, Yuanhao Chen, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci

Paul M. Thompson, Arthur W. Toga, Zhuowen Tu, 2006, MICCAI.

Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training

A. Yuille, E. Fishman, S. Bai, 2018 .

Modeling the spacing effect in sequential category learning

Alan L. Yuille, Hongjing Lu, Matthew Weiden, 2009, NIPS.

Probabilistic Motion Estimation Based on Temporal Coherence

A. Yuille, N. Grzywacz, Pierre-Yves Burgi, 2000, Neural Computation.

∗ To whom correspondence should be addressed.

A. Yuille, N. Grzywacz, Pierre-Yves Burgi, 2002 .

Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT

A. Yuille, D. Dreizin, N. Tirada, 2019, Journal of Digital Imaging.

Technical Introduction: A primer on probabilistic inference

A. Yuille, T. Griffiths, 2008 .

Recursive segmentation and recognition templates for image parsing

A. Yuille, Long Zhu, Yuanhao Chen, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Recursive Segmentation and Recognition Templates for 2D Parsing

A. Yuille, Long Zhu, Yuanhao Chen, 2008, NIPS.

The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters

Alan L. Yuille, A. Yuille, 2004, NIPS.

Multiple Instance Visual-Semantic Embedding

Zhe L. Lin, A. Yuille, Hailin Jin, 2017, BMVC.

Modeling Image Patches with a Generic Dictionary of Mini-epitomes

A. Yuille, Liang-Chieh Chen, G. Papandreou, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Adding 3D Geometry Control to Diffusion Models

A. Yuille, Angtian Wang, Yaoyao Liu, 2023, ArXiv.

Unsupervised Learning of Probabilistic Grammar-Markov Models for Object Categories

A. Yuille, Yuanhao Chen, Leo Zhu, 2007 .

Unsupervised Learning of Probabilistic Grammar-Markov Models for Object Categories Long (

A. Yuille, Yuanhao Chen, Leo Zhu, 2007 .

A Double-Loop Algorithm to Minimize the Bethe Free Energy

Alan L. Yuille, A. Yuille, 2001, EMMCVPR.

Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search

A. Yuille, Yutong Bai, Adam Kortylewski, 2023, 2306.00974.

Patch-based 3D Human Pose Refinement pdf

Alan L. Yuille, Weichao Qiu, Qingfu Wan, 2019, CVPR Workshops.

Efficient optimization of a deformable template using dynamic programming

Daniel Snow, Alan L. Yuille, James M. Coughlan, 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

Twenty Questions, Focus of Attention, and A*: A Theoretical Comparison of Optimization Strategies

Alan L. Yuille, James M. Coughlan, A. Yuille, 1997, EMMCVPR.

Learning Object Representation form Lighting Variations

Alan L. Yuille, Peter N. Belhumeur, Russell Epstein, 1996, Object Representation in Computer Vision.

Image Parsing: Segmentation, Detection, and Recognition

Zhuowen Tu, Alan L. Yuille, Song-Chun Zhu, 2003 .

Occluded Video Instance Segmentation: A Benchmark

Song Bai, Jiyang Qi, Xinggang Wang, 2021, International Journal of Computer Vision.

A Novel Linelet-Based Representation for Line Segment Detection

A. Yuille, Nam-Gyu Cho, Seong-Whan Lee, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Recovering object surfaces from viewed changes in surface texture patterns

Alan L. Yuille, Peter N. Belhumeur, P. Belhumeur, 1995, Proceedings of IEEE International Conference on Computer Vision.

Multispectral Video Semantic Segmentation: A Benchmark Dataset and Baseline

A. Yuille, Li Cheng, Cheng Bian, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans

A. Yuille, Jingren Zhou, Le Lu, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks

A. Yuille, Zongwei Zhou, Yucheng Tang, 2023, 2305.09666.

Stereo and controlled movement

Alan L. Yuille, Davi Geiger, A. Yuille, 1990, International Journal of Computer Vision.

Stereo and eye movement

D. Geiger, A. Yuille, A. Yuille, 1989, Biological Cybernetics.

Ground-Truth Data Set and Baseline Evaluations for Base-Detail Separation Algorithms at the Part Level

Alan L. Yuille, Weichao Qiu, Xuan Dong, 2018, IEEE Transactions on Circuits and Systems for Video Technology.

Ground-truth dataset and baseline evaluations for image base-detail separation algorithms pdf

Weichao Qiu, Alan Yuille, Boyan Bonev, 2015, ArXiv.

SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation

Cihang Xie, A. Yuille, Yuyin Zhou, 2023, MICCAI.

Bridging the Gap Between 2D and 3D Organ Segmentation

Alan L. Yuille, Yingda Xia, Elliot K. Fishman, 2018, MICCAI.

The Convergence of Contrastive Divergences

A. Yuille, 2004, NIPS.

UnrealStereo: Controlling Hazardous Factors to Analyze Stereo Vision

Xiaolin Hu, Yi Zhang, Alan L. Yuille, 2016, 2018 International Conference on 3D Vision (3DV).

Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-Fine Framework and Its Adversarial Examples

Yingwei Li, Alan L. Yuille, Yingda Xia, 2020, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.

Manuscript Submitted to Ieee Transactions on Medical Imaging. Do Not Distribute. Efficient Multilevel Brain Tumor Segmentation with Integrated Bayesian Model Classification

Jason J. Corso, A. Yuille, S. Dube, 2022 .

Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors pdf

Wei Shen, Elliot K. Fishman, Alan L. Yuille, 2020, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

Classification of spatially unaligned fMRI scans

Ariana E. Anderson, Mark S. Cohen, A. Yuille, 2010, NeuroImage.

Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation

A. Yuille, Song-Chun Zhu, 1996, IEEE Trans. Pattern Anal. Mach. Intell..

Region-based temporally consistent video post-processing

Alan L. Yuille, Yu Zhu, Boyan Bonev, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Deep Nets: What have They Ever Done for Vision?

A. Yuille, Chenxi Liu, 2018, International Journal of Computer Vision.

NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation

A. Yuille, Angtian Wang, Adam Kortylewski, 2021, ICLR.

Region Competition and its Analysis: A Unified Theory for Image Segmentation

Song-Chun Zhu, Alan Yuille, A. Yuille, 1995 .

Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion

A. Yuille, Long Zhu, Yuanhao Chen, 2008, ECCV.

Multilevel Detection of Stereo Disparity Surfaces

Alan L. Yuille, Yibing Yang, A. Yuille, 1993, Partitioning Data Sets.

A Part-Based, Multiresolution, TensorFaces Approach to Image-Based Facial Veriﬁcation

M. Alex O. Vasilescu, A. Yuille, Demetri Terzopoulos, 2016 .

An Alarm System for Segmentation Algorithm Based on Shape Model

Dong Yang, Daguang Xu, Alan L. Yuille, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Perception as Bayesian Inference: Introduction

Alan L. Yuille, David C. Knill, Daniel Kersten, 1996 .

Scale invariance without scale selection

A. Yuille, Iasonas Kokkinos, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Computational theories of low-level vision

Alan L. Yuille, S. Ullman, S. Ullman, 1990 .

Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy pdf

Alan Yuille, Jing Xiao, Le Lu, 2020, MICCAI.

Nuisance-Label Supervision: Robustness Improvement by Free Labels

Zihao Xiao, Weichao Qiu, Alan Yuille, 2021, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

Motion estimation by Swendsen-Wang Cuts

Adrian Barbu, Alan L. Yuille, A. Yuille, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Configural processing in biological motion detection: Human versus ideal observers

A. Yuille, Hongjing Lu, Zili Liu, 2010 .