E. Learned-Miller

Yee Whye Teh, David A. Forsyth, Ryan White, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Associating grasp configurations with hierarchical features in convolutional neural networks

Roderic A. Grupen, Li Yang Ku, Erik G. Learned-Miller, 2016, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

The UMass Mobile Manipulator UMan: An Experimental Platform for Autonomous Mobile Manipulation

Oliver Brock, Brendan Burns, Thomas Buckley, 2006 .

Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering

Christopher Joseph Pal, Erik G. Learned-Miller, David Kulp, 2007, BMC Bioinformatics.

SHREC ’ 17 Track Large-Scale 3 D Shape Retrieval from ShapeNet Core 55

Hao Su, E. Learned-Miller, D. Cohen-Or, 2016 .

Distribution Fields

E. Learned-Miller, Laura Sevilla-Lara, 2011 .

Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation

Allen R. Hanson, Erik G. Learned-Miller, Jerod J. Weinman, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Multi-view Convolutional Neural Networks for 3D Shape Recognition

Subhransu Maji, Hang Su, Evangelos Kalogerakis, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

A discriminative semi-Markov model for robust scene text recognition

Allen R. Hanson, Erik G. Learned-Miller, Jerod J. Weinman, 2008, 2008 19th International Conference on Pattern Recognition.

Faces and names in the news

Yee Whye Teh, Tim Miller, Alexander C. Berg, 2004, CVPR 2004.

Learning to Locate Informative Features for Visual Identification

Erik G. Learned-Miller, Jitendra Malik, Andras Ferencz, 2008, International Journal of Computer Vision.

The Aspect Transition Graph: An Affordance-Based Model

Roderic A. Grupen, Li Yang Ku, Erik G. Learned-Miller, 2014, ECCV Workshops.

Image classification with bags of local features

E. Learned-Miller, D. Lisin, 2006 .

Labeled Faces in the Wild : Updates and New Reporting Procedures

Erik Learned-Miller, Gary B. Huang, E. Learned-Miller, 2014 .

Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images

E. Learned-Miller, M. Parente, Tejas Panambur, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

The Processing and Analysis of in situ Gene Expression Images of the Mouse Brain

E. Learned-Miller, D. Kulp, Manjunatha Jagalur, 2006 .

Distribution Fields for Tracking ( Draft )

E. Learned-Miller, Laura Sevilla-Lara, 2012 .

Weakly supervised learning for unconstrained face processing

Erik Learned-Miller, Gary B. Huang, E. Learned-Miller, 2012 .

Object Manipulation Based on Memory and Observation

R. Grupen, E. Learned-Miller, L. Ku, 2015 .

FACIAL RECOGNITION TECHNOLOGIES IN THE WILD: A CALL FOR A FEDERAL OFFICE

E. Learned-Miller, Vicente Ordonez, Jamie H. Morgenstern, 2020 .

Improving Recognition of Novel Input with Similarity

Erik G. Learned-Miller, Jerod J. Weinman, E. Learned-Miller, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Cryptogram Decoding for OCR Using Numerization Strings

Gary B. Huang, E. Learned-Miller, A. McCallum, 2007, IEEE International Conference on Document Analysis and Recognition.

Names and faces in the news

Tamara L. Berg, A. Berg, Y. Teh, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation

E. Learned-Miller, Subhransu Maji, Aruni RoyChowdhury, 2021, Comput. Graph. Forum.

Supervised Learning and Bayesian Classification

E. Learned-Miller, 2009 .

A New Approach to Magnetic Resonance Imaging for Early Diagnosis of Alzheimer ’ s Disease

E. Learned-Miller, E. Riseman, J. Horowitz, 2009 .

Cross-Ssupervised Object Detection

Jiahui Yu, Erik Learned-Miller, Zhiqiang Shen, 2020 .

Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners

E. Learned-Miller, Hengshuang Zhao, Chuang Gan, 2022, ArXiv.

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Santhosh K. Ramakrishnan, Gautam K. Vallabha, Praveen K. Pilly, 2023, Neural Networks.

Learning class-specific image transformations with higher-order Boltzmann machines

Erik G. Learned-Miller, Gary B. Huang, E. Learned-Miller, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.

Universal Off-Policy Evaluation pdf

Bruno Castro da Silva, Scott Niekum, Philip S. Thomas, 2021, NeurIPS.

Concentration Inequalities for Conditional Value at Risk

Philip S. Thomas, Erik G. Learned-Miller, P. Thomas, 2019, ICML.

Half&Half: New Tasks and Benchmarks for Studying Visual Common Sense

Hang Su, Li Hong, Huaizu Jiang, 2019, CVPR Workshops.

Error detection and surprise in stochastic robot actions

Roderic A. Grupen, Li Yang Ku, Erik G. Learned-Miller, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Distribution fields for tracking

Laura Sevilla-Lara, Erik G. Learned-Miller, E. Learned-Miller, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Imaging cellulose synthase motility during primary cell wall synthesis in the grass Brachypodium distachyon

B. L. Hancock, E. Learned-Miller, T. Baskin, 2017, Scientific Reports.

In Defense of Grid Features for Visual Question Answering

Xinlei Chen, Marcus Rohrbach, E. Learned-Miller, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Early diagnosis of acromegaly: computers vs clinicians

Volker Blanz, Ralph E. Miller, Angela Paisley, 2011, Clinical endocrinology.

Sign Classification using Local and Meta-Features

Allen R. Hanson, Marwan A. Mattar, Erik G. Learned-Miller, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

Sign Classification for the Visually Impaired

Allen R. Hanson, Marwan A. Mattar, Erik Learned-Miller, 2005 .

Associating Grasping with Convolutional Neural Network Features pdf

Roderic A. Grupen, Li Yang Ku, Erik G. Learned-Miller, 2016, ArXiv.

Forensic Triage for Mobile Phones with DEC0DE

Brian Neil Levine, Erik G. Learned-Miller, Robert J. Walls, 2011, USENIX Security Symposium.

A Framework for Dexterous Manipulation

Julia Badger, Li Yang Ku, Jonathan Rogers, 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Passage Retrieval for Outside-Knowledge Visual Question Answering

W. Bruce Croft, Hamed Zamani, Liu Yang, 2021, SIGIR.

Reducing Duplicate Filters in Deep Neural Networks

E. Learned-Miller, Aruni RoyChowdhury, Prakhar Sharma, 2018 .

Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation

Jan Kautz, Varun Jampani, Deqing Sun, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Automatic Adaptation of Object Detectors to New Domains Using Self-Training

Liangliang Cao, Huaizu Jiang, Erik G. Learned-Miller, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Data driven image models through continuous joint alignment

Erik G. Learned-Miller, E. Learned-Miller, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

DCVNet: Dilated Cost Volume Networks for Fast Optical Flow pdf

Erik Learned-Miller, Huaizu Jiang, E. Learned-Miller, 2021, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Face Detection with the Faster R-CNN

Huaizu Jiang, Erik G. Learned-Miller, E. Learned-Miller, 2016, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).

Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples

Andrew McCallum, Erik G. Learned-Miller, Haw-Shiuan Chang, 2017, NIPS.

From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted Indexing

W. Bruce Croft, Jaap Kamps, Hamed Zamani, 2018, CIKM.

Pixel-Adaptive Convolutional Neural Networks

Hang Su, Jan Kautz, Varun Jampani, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling

Honglak Lee, Erik G. Learned-Miller, Kihyuk Sohn, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data pdf

Daniel Sheldon, Guillermo Gallego, Erik Learned-Miller, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Coherent Motion Segmentation in Moving Camera Videos Using Optical Flow Orientations

Allen R. Hanson, Erik G. Learned-Miller, Manjunath Narayana, 2013, 2013 IEEE International Conference on Computer Vision.

SENSE: A Shared Encoder Network for Scene-Flow Estimation

Jan Kautz, Varun Jampani, Deqing Sun, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos pdf

Erik G. Learned-Miller, Pia Bideau, E. Learned-Miller, 2016, ECCV.

Combining Local and Global Image Features for Object Class Recognition

Matthew B. Blaschko, Marwan A. Mattar, Erik G. Learned-Miller, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

Event Camera-based Visual Odometry for Dynamic Motion Tracking of a Legged Robot Using Adaptive Time Surface

E. Learned-Miller, Donghyun Kim, Shifan Zhu, 2023, arXiv.org.

The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields

C. Schmid, E. Learned-Miller, Alahari Karteek, 2022, International Journal of Computer Vision.

Self-Supervised Relative Depth Learning for Urban Scene Understanding

Gregory Shakhnarovich, Huaizu Jiang, Michael Maire, 2017, ECCV.

Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions

Subhransu Maji, Liangliang Cao, Evangelos Kalogerakis, 2020, ECCV.

Towards unconstrained face recognition

Erik G. Learned-Miller, Gary B. Huang, Manjunath Narayana, 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

Joint MRI Bias Removal Using Entropy Minimization Across Images

Parvez Ahammad, Erik G. Learned-Miller, E. Learned-Miller, 2004, NIPS.

Development of a Computer Vision System to Identify Sea Lamprey at Barrier Traps and Fishway

Subhransu Maji, Alex Haro, Erik Learned-Miller, 2017 .

Introduction to the Special Section on Real-World Face Recognition

Gang Hua, David J. Kriegman, Thomas S. Huang, 2011, IEEE Trans. Pattern Anal. Mach. Intell..

Using context to enhance the understanding of face images

Erik Learned-Miller, Vidit Jain, E. Learned-Miller, 2010 .

Efficient Population Registration of 3D Data

W. Eric L. Grimson, William M. Wells, Erik G. Learned-Miller, 2005, CVBIA.

End-to-End Face Detection and Cast Grouping in Movies Using Erdös-Rényi Clustering

Hang Su, Erik G. Learned-Miller, Chris Stauffer, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

MoA-Net: Self-supervised Motion Segmentation

Erik G. Learned-Miller, Pia Bideau, Rakesh R. Menon, 2018, ECCV Workshops.

The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation

Erik G. Learned-Miller, Pia Bideau, Aruni RoyChowdhury, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

A Detailed Rubric for Motion Segmentation pdf

Erik G. Learned-Miller, Pia Bideau, E. Learned-Miller, 2016, ArXiv.

Cryptogram decoding for optical character recognition

Andrew McCallum, Erik Learned-Miller, Gary B. Huang, 2006 .

Shot in the Dark: Few-Shot Learning with No Base-Class Labels pdf

Subhransu Maji, Erik Learned-Miller, Zitian Chen, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Self-Supervised Depth Learning for Urban Scene Understanding pdf

Gregory Shakhnarovich, Huaizu Jiang, Michael Maire, 2017, ArXiv.

An Efficient General-Purpose Modular Vision Model via Multi-Task Heterogeneous Training

E. Learned-Miller, M. Tomizuka, W. Zhan, 2023, ArXiv.

People-LDA: Anchoring Topics to People using Face Recognition

Andrew McCallum, Erik G. Learned-Miller, Vidit Jain, 2007, 2007 IEEE 11th International Conference on Computer Vision.

C-14: assured timestamps for drone videos

Mark D. Corner, Zhipeng Tang, Erik Learned-Miller, 2020, MobiCom.

DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures

Chun Yang, Xu-Cheng Yin, Erik Learned-Miller, 2015, PloS one.

Tight Coupling of Character, Word, and Place Recognition for End-to-End Text Recognition in Maps

Aruni Roy Chowdhury, Jerod J. Weinman, E. Learned-Miller, 2019 .

Improving Face Recognition by Clustering Unlabeled Faces in the Wild

Xiang Yu, Erik Learned-Miller, Manmohan Chandraker, 2020, ECCV.

Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics

Allen R. Hanson, Marwan A. Mattar, Erik G. Learned-Miller, 2012, UAI.

Learning on the fly: a font-free approach toward multilingual OCR

David A. Smith, Erik G. Learned-Miller, Andrew Kae, 2011, International Journal on Document Analysis and Recognition (IJDAR).

One-to-many face recognition with bilinear CNNs

Subhransu Maji, Erik G. Learned-Miller, Tsung-Yu Lin, 2015, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).

The Shape-Time Random Field for Semantic Video Labeling

Benjamin M. Marlin, Erik G. Learned-Miller, Andrew Kae, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Image registration: Maximum likelihood, minimum entropy and deep learning

Parvin Mousavi, Alireza Sedghi, Tina Kapur, 2020, Medical Image Anal..

Background subtraction: separating the modeling and the inference

Allen R. Hanson, Erik G. Learned-Miller, Manjunath Narayana, 2013, Machine Vision and Applications.

Background modeling using adaptive pixelwise kernel variances in a hybrid feature space

Allen R. Hanson, Erik G. Learned-Miller, Manjunath Narayana, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Techniques and Applications for Persistent Backgrounding in a Humanoid Torso Robot

Erik G. Learned-Miller, Jerod J. Weinman, David Walker Duhon, 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

Improvements in Joint Domain-Range Modeling for Background Subtraction

Allen R. Hanson, Erik G. Learned-Miller, Manjunath Narayana, 2012, BMVC.

Face Identification with Bilinear CNNs pdf

Subhransu Maji, Erik G. Learned-Miller, Tsung-Yu Lin, 2015, ArXiv.

An aspect representation for object manipulation based on convolutional neural networks

Roderic A. Grupen, Li Yang Ku, Erik G. Learned-Miller, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Detecting Acromegaly: Screening for Disease with a Morphable Model

Qifeng Lu, Erik G. Learned-Miller, Volker Blanz, 2006, MICCAI.

Improved Generative Models for Continuous Image Features through Tree-structured Non-parametric Distributions

Marwan A. Mattar, Erik Learned-Miller, Marwan Mattar, 2006 .

A Probabilistic Upper Bound on Differential Entropy

Erik G. Learned-Miller, Joseph DeStefano, E. Learned-Miller, 2005, IEEE Transactions on Information Theory.

Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions

E. Learned-Miller, Subhransu Maji, Aruni RoyChowdhury, 2020, ECCV.

Half-Wits: Software Techniques for Low-Voltage Probabilistic Storage on Microcontrollers with NOR Flash Memory

Yue Wang, Anxiao Jiang, Kevin Fu, 2013, TECS.

Exploiting Half-Wits: Smarter Storage for Low-Power Devices

Yue Wang, Anxiao Jiang, Kevin Fu, 2011, FAST.

It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos

E. Learned-Miller, Pia Bideau, 2016, ECCV.

Unsupervised Hard Example Mining from Videos for Improved Object Detection pdf

Aditya Prasad, Huaizu Jiang, Erik G. Learned-Miller, 2018, ECCV.

Learning on the Fly: Font-Free Approaches to Difficult OCR Problems

E. Learned-Miller, Andrew Kae, 2009, 2009 10th International Conference on Document Analysis and Recognition.

Learning hierarchical representations for face verification with convolutional deep belief networks

Honglak Lee, Erik Learned-Miller, Gary B. Huang, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation

Jerod J. Weinman, E. Learned-Miller, A. Hanson, 2022 .

Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners

E. Learned-Miller, Hengshuang Zhao, Chuang Gan, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Joint Feature Selection for Object Detection and Recognition

Allen R. Hanson, Erik Learned-Miller, Jerod J. Weinman, 2006 .

In Defense of Grid Features for Visual Question Answering

Xinlei Chen, Marcus Rohrbach, E. Learned-Miller, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Scene Text Recognition with Bilateral Regression

Erik Learned-Miller, Jacqueline L. Feild, Jacqueline Feild, 2012 .

Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging

E. Learned-Miller, E. Kalogerakis, J. Priest, 2023, MICCAI.

S UPPLEMENTARY M ATERIAL OF Self-Supervised Relative Depth Learning for Urban Scene Understanding

M. Maire, E. Learned-Miller, Gregory Shakhnarovich, 2022 .

Towards Practical Mean Bounds for Small Samples

Philip S. Thomas, Erik Learned-Miller, My Phan, 2021, ICML.

A New Confidence Interval for the Mean of a Bounded Random Variable pdf

Philip S. Thomas, Erik G. Learned-Miller, P. Thomas, 2019, ArXiv.