Rob Fergus

发表

Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories

Pietro Perona, Fei-Fei Li, Rob Fergus, 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

Convolutional Learning of Spatio-temporal Features

Yann LeCun, Christoph Bregler, Graham W. Taylor, 2010, ECCV.

A Hybrid Neural Network-Latent Topic Model

Long Zhu, Li Wan, Rob Fergus, 2012, AISTATS.

Object Recognition by Scene Alignment

Antonio Torralba, William T. Freeman, Ce Liu, 2007, NIPS.

End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression

Li Wan, Rob Fergus, David Eigen, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Understanding Deep Architectures using a Recursive Convolutional Network pdf

Yann LeCun, Rob Fergus, David Eigen, 2013, ICLR.

MazeBase: A Sandbox for Learning from Games pdf

Rob Fergus, Soumith Chintala, Arthur Szlam, 2015, ArXiv.

Fast Image Deconvolution using Hyper-Laplacian Priors

Rob Fergus, Dilip Krishnan, R. Fergus, 2009, NIPS.

Removing camera shake from a single photograph

William T. Freeman, Aaron Hertzmann, Rob Fergus, 2006, ACM Trans. Graph..

Deconvolutional networks

Graham W. Taylor, Rob Fergus, Dilip Krishnan, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Intriguing properties of neural networks pdf

Joan Bruna, Dumitru Erhan, Wojciech Zaremba, 2013, ICLR.

Improving Image Classification with Location Context

Fei-Fei Li, Rob Fergus, Manohar Paluri, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Efficient methods for object recognition using the constellation model

Pietro Perona, Rob Fergus, Markus Weber, 2001 .

Sampling Methods for Unsupervised Learning

Pietro Perona, Andrew Zisserman, Rob Fergus, 2004, NIPS.

Case for Automated Detection of Diabetic Retinopathy

Lakshminarayanan Subramanian, Nathan Silberman, Rob Fergus, 2010, AAAI Spring Symposium: Artificial Intelligence for Development.

Learning Spatiotemporal Features with 3D Convolutional Networks

Lorenzo Torresani, Du Tran, Rob Fergus, 2014, 2015 IEEE International Conference on Computer Vision (ICCV).

Composable Planning with Attributes pdf

Rob Fergus, Arthur Szlam, Sainbayar Sukhbaatar, 2018, ICML.

Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks pdf

Rob Fergus, Sam Gross, Emily L. Denton, 2016, ArXiv.

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play pdf

Ilya Kostrikov, Rob Fergus, Arthur Szlam, 2017, ICLR.

Indoor Segmentation and Support Inference from RGBD Images

Derek Hoiem, Pushmeet Kohli, Nathan Silberman, 2012, ECCV.

Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition

Pietro Perona, Andrew Zisserman, Rob Fergus, 2007, International Journal of Computer Vision.

Indoor scene segmentation using a structured light sensor

Nathan Silberman, Rob Fergus, R. Fergus, 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

Object class recognition by unsupervised scale-invariant learning

Pietro Perona, Andrew Zisserman, Rob Fergus, 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

Blind deconvolution using a normalized sparsity measure

Rob Fergus, Dilip Krishnan, Terence Tay, 2011, CVPR 2011.

Beyond frontal faces: Improving Person Recognition using multiple cues

Ning Zhang, Rob Fergus, Yaniv Taigman, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies

Abhinav Gupta, Rob Fergus, Arthur Szlam, 2019, ICLR.

Semantic Label Sharing for Learning with Many Categories

Antonio Torralba, Rob Fergus, Yair Weiss, 2010, ECCV.

Visualizing and Understanding Convolutional Networks

Rob Fergus, Matthew D. Zeiler, R. Fergus, 2013, ECCV.

Instance Segmentation of Indoor Scenes Using a Coverage Loss

Nathan Silberman, Rob Fergus, David Sontag, 2014, ECCV.

A Sparse Object Category Model for Efficient Learning and Complete Recognition

Pietro Perona, Andrew Zisserman, Rob Fergus, 2006, Toward Category-Level Object Recognition.

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

Joan Bruna, Yann LeCun, Wojciech Zaremba, 2014, NIPS.

Learning Binary Hash Codes for Large-Scale Image Search

Kristen Grauman, Rob Fergus, R. Fergus, 2013, Machine Learning for Computer Vision.

Learning to Discover Efficient Mathematical Identities

Wojciech Zaremba, Rob Fergus, Karol Kurach, 2014, NIPS.

Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels pdf

Ilya Kostrikov, Rob Fergus, Denis Yarats, 2020, ArXiv.

Deep Poselets for Human Detection pdf

Fei Yang, Rob Fergus, Lubomir D. Bourdev, 2014, ArXiv.

Nonparametric image parsing using adaptive neighbor sets

Rob Fergus, David Eigen, R. Fergus, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

End-To-End Memory Networks

Jason Weston, Rob Fergus, Arthur Szlam, 2015, NIPS.

Differentiable Pooling for Hierarchical Feature Learning pdf

Rob Fergus, Matthew D. Zeiler, R. Fergus, 2012, ArXiv.

Disentangling Video with Independent Prediction pdf

Rob Fergus, William F. Whitney, 2019, ArXiv.

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning pdf

Ilya Kostrikov, Rob Fergus, Denis Yarats, 2020, ArXiv.

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture

Rob Fergus, David Eigen, R. Fergus, 2014, 2015 IEEE International Conference on Computer Vision (ICCV).

Regularization of Neural Networks using DropConnect

Yann LeCun, Li Wan, Rob Fergus, 2013, ICML.

Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning pdf

Rob Fergus, Arthur Szlam, Sainbayar Sukhbaatar, 2018, ArXiv.

Learning from Noisy Labels with Deep Neural Networks pdf

Rob Fergus, Sainbayar Sukhbaatar, R. Fergus, 2014, ICLR.

Multidimensional Spectral Hashing

Antonio Torralba, Rob Fergus, Yair Weiss, 2012, ECCV.

Finding Generalizable Evidence by Learning to Convince Q&A Models pdf

Jason Weston, Kyunghyun Cho, Rob Fergus, 2019, EMNLP.

Image and depth from a conventional camera with a coded aperture

Frédo Durand, William T. Freeman, Rob Fergus, 2007, SIGGRAPH 2007.

Energy-based models for atomic-resolution protein conformations pdf

Rob Fergus, Yilun Du, Jerry Ma, 2020, ICLR.

Learning by Asking Questions

Martial Hebert, Abhinav Gupta, Laurens van der Maaten, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Stochastic Pooling for Regularization of Deep Convolutional Neural Networks pdf

Rob Fergus, Matthew D. Zeiler, R. Fergus, 2013, ICLR.

Web scale photo hash clustering on a single machine

Fei Yang, Rob Fergus, Lubomir D. Bourdev, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Weakly Supervised Memory Networks pdf

Jason Weston, Rob Fergus, Arthur Szlam, 2015, ArXiv.

Fast Adaptation via Policy-Dynamics Value Functions

Rob Fergus, Arthur Szlam, Roberta Raileanu, 2020, ICML.

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network

Rob Fergus, David Eigen, Christian Puhrsch, 2014, NIPS.

Removing camera shake from a single photograph

William T. Freeman, Aaron Hertzmann, Rob Fergus, 2006, SIGGRAPH 2006.

Visualizing and Understanding Convolutional Neural Networks

Rob Fergus, Matthew D. Zeiler, R. Fergus, 2013 .

Learning Multiagent Communication with Backpropagation

Rob Fergus, Arthur Szlam, Sainbayar Sukhbaatar, 2016, NIPS.

Blind Deconvolution with Non-local Sparsity Reweighting

Joan Bruna, Rob Fergus, Dilip Krishnan, 2013, 1311.4029.

User Conditional Hashtag Prediction for Images

Emily Denton, Jason Weston, Rob Fergus, 2015, KDD.

Learning invariant features through topographic filter maps

Marc'Aurelio Ranzato, Yann LeCun, Koray Kavukcuoglu, 2009, CVPR.

Adaptive deconvolutional networks for mid and high level feature learning

Graham W. Taylor, Rob Fergus, Matthew D. Zeiler, 2011, 2011 International Conference on Computer Vision.

Learning object categories from Google's image search

Pietro Perona, Fei-Fei Li, Andrew Zisserman, 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

A Bayesian approach to unsupervised one-shot learning of object categories

Pietro Perona, Li Fei-Fei, Rob Fergus, 2003, ICCV 2003.

Low-level Image Priors and Laplacian Preconditioners for Applications in Computer Graphics and Computational Photography

Rob Fergus, Dilip Krishnan, R. Fergus, 2013 .

Modeling Others using Oneself in Multi-Agent Reinforcement Learning

Rob Fergus, Arthur Szlam, Emily L. Denton, 2018, ICML.

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

Rob Fergus, Soumith Chintala, Arthur Szlam, 2015, NIPS.

Deep Neural Networks Predict Category Typicality Ratings for Images

Wojciech Zaremba, Rob Fergus, Todd M. Gureckis, 2015, CogSci.

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks pdf

Xiang Zhang, Yann LeCun, Pierre Sermanet, 2013, ICLR.

Semi-Supervised Learning in Gigantic Image Collections

Antonio Torralba, Rob Fergus, Yair Weiss, 2009, NIPS.

Image and depth from a conventional camera with a coded aperture

Frédo Durand, William T. Freeman, Rob Fergus, 2007, ACM Trans. Graph..

Spectral Hashing

Antonio Torralba, Rob Fergus, Yair Weiss, 2008, NIPS.

C3D: Generic Features for Video Analysis pdf

Lorenzo Torresani, Du Tran, Rob Fergus, 2014, ArXiv.

Deconvolutional Networks for Feature Learning

Graham W. Taylor, Rob Fergus, Dilip Krishnan, 2010 .

Ieee Transactions on Pattern Analysis and Machine Intelligence 1 80 Million Tiny Images: a Large Dataset for Non-parametric Object and Scene Recognition

Antonio Torralba, William T. Freeman, Rob Fergus, 2022 .

Blind Deconvolution with Re-weighted Sparsity Promotion pdf

Joan Bruna, Rob Fergus, Dilip Krishnan, 2013, ArXiv.

Visual object category recognition

Rob Fergus, R. Fergus, 2005 .

Empirically Verifying Hypotheses Using Reinforcement Learning pdf

Abhinav Gupta, Rob Fergus, Arthur Szlam, 2020, ArXiv.

Dark flash photography

Rob Fergus, Dilip Krishnan, 2009, ACM Trans. Graph..

Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories

Pietro Perona, Fei-Fei Li, Rob Fergus, 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

Differentiable pooling for hierarchical feature learning: arXiv 1207.0151v1

Rob Fergus, Matthew D. Zeiler, R. Fergus, 2012 .

Stochastic Video Generation with a Learned Prior

Rob Fergus, Emily L. Denton, R. Fergus, 2018, ICML.

A Bayesian approach to unsupervised one-shot learning of object categories

Pietro Perona, Fei-Fei Li, Rob Fergus, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

Restoring an Image Taken through a Window Covered with Dirt or Rain

Rob Fergus, David Eigen, Dilip Krishnan, 2013, 2013 IEEE International Conference on Computer Vision.

Learning Physical Intuition of Block Towers by Example

Rob Fergus, Sam Gross, Adam Lerer, 2016, ICML.

Simple Baseline for Visual Question Answering pdf

Yuandong Tian, Bolei Zhou, Rob Fergus, 2015, ArXiv.

Training Convolutional Networks with Noisy Labels

Joan Bruna, Rob Fergus, Manohar Paluri, 2014, ICLR 2014.

Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines

Leonid Sigal, Graham W. Taylor, Rob Fergus, 2011, NIPS.

Learning binary projections for large scale image search

Kristen Grauman, Rob Fergus, R. Fergus, 2011 .

Learning Object Categories From Internet Image Searches

Pietro Perona, Fei-Fei Li, Andrew Zisserman, 2010, Proceedings of the IEEE.

A Visual Category Filter for Google Images

Pietro Perona, Andrew Zisserman, Rob Fergus, 2004, ECCV.

Understanding the Asymptotic Performance of Model-Based RL Methods

Rob Fergus, William F. Whitney, R. Fergus, 2018 .

Learning invariance through imitation

Christoph Bregler, Graham W. Taylor, Rob Fergus, 2011, CVPR 2011.

One-shot learning of object categories

Pietro Perona, Fei-Fei Li, Rob Fergus, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Learning Object Categories From Internet Image Searches This paper shows how the results returned by an image search engine can be used to construct models from Internet images and use them for object recognition.

Pietro Perona, Andrew Zisserman, Rob Fergus, 2010 .

Object and scene recognition in tiny images

Antonio Torralba, William T. Freeman, Rob Fergus, 2010 .

IntPhys: A Framework and Benchmark for Visual Intuitive Physics Reasoning pdf

Emmanuel Dupoux, Rob Fergus, Mathieu Bernard, 2018, ArXiv.

Small codes and large image databases for recognition

Antonio Torralba, Rob Fergus, Yair Weiss, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Deep End2End Voxel2Voxel Prediction

Lorenzo Torresani, Du Tran, Rob Fergus, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images pdf

Joelle Pineau, Ilya Kostrikov, Rob Fergus, 2019, ArXiv.

Learning Simple Algorithms from Examples

Wojciech Zaremba, Tomas Mikolov, Armand Joulin, 2015, ICML.

A sparse object category model for efficient learning and exhaustive recognition

Pietro Perona, Andrew Zisserman, Rob Fergus, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Pose-Sensitive Embedding by Nonlinear NCA Regression

Christoph Bregler, Graham W. Taylor, Rob Fergus, 2010, NIPS.

Fast Adaptation via Policy-Dynamics Value Functions pdf

Rob Fergus, Arthur Szlam, Roberta Raileanu, 2020, ArXiv.

Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Ilya Kostrikov, Jonathan Tompson, Rob Fergus, 2021, ICML.

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Joelle Pineau, Ilya Kostrikov, Rob Fergus, 2019, AAAI.

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Tom Sercu, Myle Ott, Rob Fergus, 2021, Proceedings of the National Academy of Sciences.

Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning pdf

Alessandro Lazaric, Rob Fergus, Denis Yarats, 2021, ICLR.

Decoupling Value and Policy for Generalization in Reinforcement Learning pdf

Rob Fergus, Roberta Raileanu, R. Fergus, 2021, ICML.

Imitation by Predicting Observations

Andrew Jaegle, Rob Fergus, Arun Ahuja, 2021, ICML.

Reinforcement Learning with Prototypical Representations

Alessandro Lazaric, Rob Fergus, Denis Yarats, 2021, ICML.

Deep End2End Voxel2Voxel Prediction

Lorenzo Torresani, Du Tran, Rob Fergus, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

IntPhys 2019: A Benchmark for Visual Intuitive Physics Understanding

Emmanuel Dupoux, Rob Fergus, Adam Lerer, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.