Rob Fergus

According to our database, Rob Fergus authored at least 115 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Training Language Models on Synthetic Edit Sequences Improves Code Synthesis.

Ulyana Piterbarg, Lerrel Pinto, Rob Fergus

CoRR, 2024

Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction.

Anthony GX-Chen, Kenneth Marino, Rob Fergus

CoRR, 2024

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs.

Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, Austin Wang, Rob Fergus, Yann LeCun, Saining Xie

CoRR, 2024

diff History for Neural Language Agents.

Ulyana Piterbarg, Lerrel Pinto, Rob Fergus

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks.

Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval.

Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders.

Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

diff History for Long-Context Language Agents.

Ulyana Piterbarg, Lerrel Pinto, Rob Fergus

CoRR, 2023

Hierarchical reinforcement learning with natural language subgoals.

Arun Ahuja, Kavya Kopparapu, Rob Fergus, Ishita Dasgupta

CoRR, 2023

Accelerating exploration and representation learning with offline pre-training.

Bogdan Mazoure, Jake Bruce, Doina Precup, Rob Fergus, Ankit Anand

CoRR, 2023

Collaborating with language models for embodied reasoning.

Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, Arun Ahuja, Sheila Babayan, Felix Hill, Rob Fergus

CoRR, 2023

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval.

Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar

CoRR, 2023

NetHack is Hard to Hack.

Ulyana Piterbarg, Lerrel Pinto, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distilling Internet-Scale Vision-Language Models into Embodied Agents.

Theodore R. Sumers, Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta

Proceedings of the International Conference on Machine Learning, 2023

Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC.

Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl

Proceedings of the International Conference on Machine Learning, 2023

Teacher Guided Training: An Efficient Framework for Knowledge Transfer.

Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning About Progress From Experts.

Jake Bruce, Ankit Anand, Bogdan Mazoure, Rob Fergus

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

IntPhys 2019: A Benchmark for Visual Intuitive Physics Understanding.

Ronan Riochet, Mario Ynocente Castro, Mathieu Bernard, Adam Lerer, Rob Fergus, Véronique Izard, Emmanuel Dupoux

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Learning to Navigate Wikipedia by Taking Random Walks.

Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

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

Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, Rob Fergus

Proc. Natl. Acad. Sci. USA, 2021

Automatic Data Augmentation for Generalization in Reinforcement Learning.

Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reinforcement Learning with Prototypical Representations.

Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto

Proceedings of the 38th International Conference on Machine Learning, 2021

Decoupling Value and Policy for Generalization in Reinforcement Learning.

Roberta Raileanu, Rob Fergus

Proceedings of the 38th International Conference on Machine Learning, 2021

Offline Reinforcement Learning with Fisher Divergence Critic Regularization.

Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum

Proceedings of the 38th International Conference on Machine Learning, 2021

Imitation by Predicting Observations.

Andrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne

Proceedings of the 38th International Conference on Machine Learning, 2021

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

Denis Yarats, Ilya Kostrikov, Rob Fergus

Proceedings of the 9th International Conference on Learning Representations, 2021

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

Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Fast Adaptation via Policy-Dynamics Value Functions.

Roberta Raileanu, Maxwell Goldstein, Arthur Szlam, Rob Fergus

CoRR, 2020

Empirically Verifying Hypotheses Using Reinforcement Learning.

Kenneth Marino, Rob Fergus, Arthur Szlam, Abhinav Gupta

CoRR, 2020

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning.

Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus

CoRR, 2020

Fast Adaptation to New Environments via Policy-Dynamics Value Functions.

Roberta Raileanu, Maxwell Goldstein, Arthur Szlam, Rob Fergus

Proceedings of the 37th International Conference on Machine Learning, 2020

Energy-based models for atomic-resolution protein conformations.

Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Disentangling Video with Independent Prediction.

William F. Whitney, Rob Fergus

CoRR, 2019

Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies.

Kenneth Marino, Abhinav Gupta, Rob Fergus, Arthur Szlam

Proceedings of the 7th International Conference on Learning Representations, 2019

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

Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

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

Sainbayar Sukhbaatar, Emily Denton, Arthur Szlam, Rob Fergus

CoRR, 2018

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

Ronan Riochet, Mario Ynocente Castro, Mathieu Bernard, Adam Lerer, Rob Fergus, Véronique Izard, Emmanuel Dupoux

CoRR, 2018

Composable Planning with Attributes.

Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer, Arthur Szlam, Rob Fergus

Proceedings of the 35th International Conference on Machine Learning, 2018

Modeling Others using Oneself in Multi-Agent Reinforcement Learning.

Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus

Proceedings of the 35th International Conference on Machine Learning, 2018

Stochastic Video Generation with a Learned Prior.

Emily Denton, Rob Fergus

Proceedings of the 35th International Conference on Machine Learning, 2018

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play.

Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, Rob Fergus

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning by Asking Questions.

Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play.

Sainbayar Sukhbaatar, Ilya Kostrikov, Arthur Szlam, Rob Fergus

CoRR, 2017

2016

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

Emily L. Denton, Sam Gross, Rob Fergus

CoRR, 2016

Learning Multiagent Communication with Backpropagation.

Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Simple Algorithms from Examples.

Wojciech Zaremba, Tomás Mikolov, Armand Joulin, Rob Fergus

Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Physical Intuition of Block Towers by Example.

Adam Lerer, Sam Gross, Rob Fergus

Proceedings of the 33nd International Conference on Machine Learning, 2016

Deep End2End Voxel2Voxel Prediction.

Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

2015

Simple Baseline for Visual Question Answering.

Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus

CoRR, 2015

Weakly Supervised Memory Networks.

Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus

CoRR, 2015

MazeBase: A Sandbox for Learning from Games.

Sainbayar Sukhbaatar, Arthur Szlam, Gabriel Synnaeve, Soumith Chintala, Rob Fergus

CoRR, 2015

Learning from Noisy Labels with Deep Neural Networks.

Sainbayar Sukhbaatar, Rob Fergus

Proceedings of the 3rd International Conference on Learning Representations, 2015

End-To-End Memory Networks.

Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks.

Emily L. Denton, Soumith Chintala, Arthur Szlam, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

User Conditional Hashtag Prediction for Images.

Emily Denton, Jason Weston, Manohar Paluri, Lubomir D. Bourdev, Rob Fergus

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Learning Spatiotemporal Features with 3D Convolutional Networks.

Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Improving Image Classification with Location Context.

Kevin D. Tang, Manohar Paluri, Li Fei-Fei, Robert Fergus, Lubomir D. Bourdev

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

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

David Eigen, Rob Fergus

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Beyond frontal faces: Improving Person Recognition using multiple cues.

Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir D. Bourdev

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

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

Li Wan, David Eigen, Rob Fergus

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Web scale photo hash clustering on a single machine.

Yunchao Gong, Marcin Pawlowski, Fei Yang, Louis Brandy, Lubomir D. Bourdev, Rob Fergus

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Deep Neural Networks Predict Category Typicality Ratings for Images.

Brenden M. Lake, Wojciech Zaremba, Rob Fergus, Todd M. Gureckis

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2014

C3D: Generic Features for Video Analysis.

Du Tran, Lubomir D. Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri

CoRR, 2014

Intriguing properties of neural networks.

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus

Proceedings of the 2nd International Conference on Learning Representations, 2014

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

Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun

Proceedings of the 2nd International Conference on Learning Representations, 2014

Understanding Deep Architectures using a Recursive Convolutional Network.

David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun

Proceedings of the 2nd International Conference on Learning Representations, 2014

Deep Poselets for Human Detection.

Lubomir D. Bourdev, Fei Yang, Rob Fergus

CoRR, 2014

Learning to Discover Efficient Mathematical Identities.

Wojciech Zaremba, Karol Kurach, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

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

David Eigen, Christian Puhrsch, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation.

Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Visualizing and Understanding Convolutional Networks.

Matthew D. Zeiler, Rob Fergus

Proceedings of the Computer Vision - ECCV 2014, 2014

Instance Segmentation of Indoor Scenes Using a Coverage Loss.

Nathan Silberman, David A. Sontag, Rob Fergus

Proceedings of the Computer Vision - ECCV 2014, 2014

2013

Learning Binary Hash Codes for Large-Scale Image Search.

Kristen Grauman, Rob Fergus

Proceedings of the Machine Learning for Computer Vision, 2013

Stochastic Pooling for Regularization of Deep Convolutional Neural Networks

Matthew D. Zeiler, Rob Fergus

Proceedings of the 1st International Conference on Learning Representations, 2013

Blind Deconvolution with Re-weighted Sparsity Promotion.

Dilip Krishnan, Joan Bruna, Rob Fergus

CoRR, 2013

Regularization of Neural Networks using DropConnect.

Li Wan, Matthew D. Zeiler, Sixin Zhang, Yann LeCun, Rob Fergus

Proceedings of the 30th International Conference on Machine Learning, 2013

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

David Eigen, Dilip Krishnan, Rob Fergus

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

A Hybrid Neural Network-Latent Topic Model.

Li Wan, Leo Zhu, Rob Fergus

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Differentiable Pooling for Hierarchical Feature Learning

Matthew D. Zeiler, Rob Fergus

CoRR, 2012

Multidimensional Spectral Hashing.

Yair Weiss, Rob Fergus, Antonio Torralba

Proceedings of the Computer Vision - ECCV 2012, 2012

Indoor Segmentation and Support Inference from RGBD Images.

Nathan Silberman, Derek Hoiem, Pushmeet Kohli, Rob Fergus

Proceedings of the Computer Vision - ECCV 2012, 2012

Nonparametric image parsing using adaptive neighbor sets.

David Eigen, Rob Fergus

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines.

Matthew D. Zeiler, Graham W. Taylor, Leonid Sigal, Iain A. Matthews, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Indoor scene segmentation using a structured light sensor.

Nathan Silberman, Rob Fergus

Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Adaptive deconvolutional networks for mid and high level feature learning.

Matthew D. Zeiler, Graham W. Taylor, Rob Fergus

Proceedings of the IEEE International Conference on Computer Vision, 2011

Learning invariance through imitation.

Graham W. Taylor, Ian Spiro, Christoph Bregler, Rob Fergus

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Blind deconvolution using a normalized sparsity measure.

Dilip Krishnan, Terence Tay, Rob Fergus

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Learning Object Categories From Internet Image Searches.

Robert Fergus, Li Fei-Fei, Pietro Perona, Andrew Zisserman

Proc. IEEE, 2010

Pose-Sensitive Embedding by Nonlinear NCA Regression.

Graham W. Taylor, Rob Fergus, George Williams, Ian Spiro, Christoph Bregler

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Convolutional Learning of Spatio-temporal Features.

Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler

Proceedings of the Computer Vision - ECCV 2010, 2010

Semantic Label Sharing for Learning with Many Categories.

Robert Fergus, Hector Bernal, Yair Weiss, Antonio Torralba

Proceedings of the Computer Vision, 2010

Deconvolutional networks.

Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, Robert Fergus

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Case for Automated Detection of Diabetic Retinopathy.

Nathan Silberman, Kristy Ahrlich, Rob Fergus, Lakshminarayanan Subramanian

Proceedings of the Artificial Intelligence for Development, 2010

2009

Dark flash photography.

Dilip Krishnan, Rob Fergus

ACM Trans. Graph., 2009

Fast Image Deconvolution using Hyper-Laplacian Priors.

Dilip Krishnan, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Semi-Supervised Learning in Gigantic Image Collections.

Rob Fergus, Yair Weiss, Antonio Torralba

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Learning invariant features through topographic filter maps.

Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergus, Yann LeCun

Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008

80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition.

Antonio Torralba, Robert Fergus, William T. Freeman

IEEE Trans. Pattern Anal. Mach. Intell., 2008

Spectral Hashing.

Yair Weiss, Antonio Torralba, Robert Fergus

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Small codes and large image databases for recognition.

Antonio Torralba, Robert Fergus, Yair Weiss

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007

Image and depth from a conventional camera with a coded aperture.

Anat Levin, Robert Fergus, Frédo Durand, William T. Freeman

ACM Trans. Graph., 2007

Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition.

Robert Fergus, Pietro Perona, Andrew Zisserman

Int. J. Comput. Vis., 2007

Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories.

Li Fei-Fei, Robert Fergus, Pietro Perona

Comput. Vis. Image Underst., 2007

Object Recognition by Scene Alignment.

Bryan C. Russell, Antonio Torralba, Ce Liu, Robert Fergus, William T. Freeman

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Removing camera shake from a single photograph.

Robert Fergus, Barun Singh, Aaron Hertzmann, Sam T. Roweis, William T. Freeman

ACM Trans. Graph., 2006

One-Shot Learning of Object Categories.

Li Fei-Fei, Robert Fergus, Pietro Perona

IEEE Trans. Pattern Anal. Mach. Intell., 2006

A Sparse Object Category Model for Efficient Learning and Complete Recognition.

Robert Fergus, Pietro Perona, Andrew Zisserman

Proceedings of the Toward Category-Level Object Recognition, 2006

2005

Visual object category recognition.

Robert Fergus

PhD thesis, 2005

Learning Object Categories from Google's Image Search.

Robert Fergus, Li Fei-Fei, Pietro Perona, Andrew Zisserman

Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV 2005), 2005

A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition.

Robert Fergus, Pietro Perona, Andrew Zisserman

Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004

Sampling Methods for Unsupervised Learning.

Robert Fergus, Andrew Zisserman, Pietro Perona

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A Visual Category Filter for Google Images.

Robert Fergus, Pietro Perona, Andrew Zisserman

Proceedings of the Computer Vision, 2004

2003

A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories.

Li Fei-Fei, Robert Fergus, Pietro Perona

Proceedings of the 9th IEEE International Conference on Computer Vision (ICCV 2003), 2003

Object Class Recognition by Unsupervised Scale-Invariant Learning.

Robert Fergus, Pietro Perona, Andrew Zisserman

Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2003), 2003