EG-RRT: Environment-guided random trees for kinodynamic motion planning with uncertainty and obstacles. - Leonard Jaillet; Judy Hoffman; Jur van den Berg; Pieter Abbeel; Josep M. Porta; Kenneth Y. Goldberg (IROS, 2011)

Weakly Supervised Learning of Object Segmentations from Web-Scale Video. - Glenn Hartmann; Matthias Grundmann; Judy Hoffman; David Tsai 002; Vivek Kwatra; Omid Madani; Sudheendra Vijayanarasimhan; Irfan A. Essa; James M. Rehg; Rahul Sukthankar (ECCV Workshops (1), 2012)

Discovering Latent Domains for Multisource Domain Adaptation. - Judy Hoffman; Brian Kulis; Trevor Darrell; Kate Saenko (ECCV (2), 2012)

Semi-supervised Domain Adaptation with Instance Constraints. - Jeff Donahue; Judy Hoffman; Erik Rodner; Kate Saenko; Trevor Darrell (CVPR, 2013)

Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations. - Erik Rodner; Judy Hoffman; Jeff Donahue; Trevor Darrell; Kate Saenko (CoRR, 2013)

Efficient Learning of Domain-invariant Image Representations - Judy Hoffman; Erik Rodner; Jeff Donahue; Kate Saenko; Trevor Darrell (ICLR (Poster), 2013)

Continuous Manifold Based Adaptation for Evolving Visual Domains. - Judy Hoffman; Trevor Darrell; Kate Saenko (CVPR, 2014)

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. - Jeff Donahue; Yangqing Jia; Oriol Vinyals; Judy Hoffman; Ning Zhang 014; Eric Tzeng; Trevor Darrell (ICML, 2014)

Interactive adaptation of real-time object detectors. - Daniel Goehring; Judy Hoffman; Erik Rodner; Kate Saenko; Trevor Darrell (ICRA, 2014)

LSDA: Large Scale Detection through Adaptation. - Judy Hoffman; Sergio Guadarrama; Eric Tzeng; Ronghang Hu; Jeff Donahue; Ross B. Girshick; Trevor Darrell; Kate Saenko (NIPS, 2014)

LSDA: Large Scale Detection Through Adaptation. - Judy Hoffman; Sergio Guadarrama; Eric Tzeng; Jeff Donahue; Ross B. Girshick; Trevor Darrell; Kate Saenko (CoRR, 2014)

One-Shot Adaptation of Supervised Deep Convolutional Models. - Judy Hoffman; Eric Tzeng; Jeff Donahue; Yangqing Jia; Kate Saenko; Trevor Darrell (ICLR (Workshop Poster), 2014)

Deep Domain Confusion: Maximizing for Domain Invariance. - Eric Tzeng; Judy Hoffman; Ning Zhang 014; Kate Saenko; Trevor Darrell (CoRR, 2014)

Asymmetric and Category Invariant Feature Transformations for Domain Adaptation. - Judy Hoffman; Erik Rodner; Jeff Donahue; Brian Kulis; Kate Saenko (Int. J. Comput. Vis., 2014)

Detector discovery in the wild: Joint multiple instance and representation learning. - Judy Hoffman; Deepak Pathak; Trevor Darrell; Kate Saenko (CVPR, 2015)

Spatial Semantic Regularisation for Large Scale Object Detection. - Damian Mrowca; Marcus Rohrbach; Judy Hoffman; Ronghang Hu; Kate Saenko; Trevor Darrell (ICCV, 2015)

Simultaneous Deep Transfer Across Domains and Tasks. - Eric Tzeng; Judy Hoffman; Trevor Darrell; Kate Saenko (ICCV, 2015)

Quantification in-the-wild: data-sets and baselines. - Oscar Beijbom; Judy Hoffman; Evan Yao; Trevor Darrell; Alberto Rodriguez-Ramirez; Manuel González-Rivero; Ove Hoegh-Guldberg (CoRR, 2015)

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. - Eric Tzeng; Coline Devin; Judy Hoffman; Chelsea Finn; Xingchao Peng; Sergey Levine; Kate Saenko; Trevor Darrell (CoRR, 2015)

Cross Modal Distillation for Supervision Transfer. - Saurabh Gupta 001; Judy Hoffman; Jitendra Malik (CVPR, 2016)

Learning with Side Information through Modality Hallucination. - Judy Hoffman; Saurabh Gupta 001; Trevor Darrell (CVPR, 2016)

Best Practices for Fine-Tuning Visual Classifiers to New Domains. - Brian Chu; Vashisht Madhavan; Oscar Beijbom; Judy Hoffman; Trevor Darrell (ECCV Workshops (3), 2016)

Clockwork Convnets for Video Semantic Segmentation. - Evan Shelhamer; Kate Rakelly; Judy Hoffman; Trevor Darrell (ECCV Workshops (3), 2016)

Fine-to-coarse knowledge transfer for low-res image classification. - Xingchao Peng; Judy Hoffman; Stella X. Yu; Kate Saenko (ICIP, 2016)

Cross-modal adaptation for RGB-D detection. - Judy Hoffman; Saurabh Gupta 001; Jian Leong; Sergio Guadarrama; Trevor Darrell (ICRA, 2016)

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints. - Eric Tzeng; Coline Devin; Judy Hoffman; Chelsea Finn; Pieter Abbeel; Sergey Levine; Kate Saenko; Trevor Darrell (WAFR, 2016)

FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation. - Judy Hoffman; Dequan Wang; Fisher Yu 001; Trevor Darrell (CoRR, 2016)

Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning. - Judy Hoffman; Deepak Pathak; Eric Tzeng; Jonathan Long; Sergio Guadarrama; Trevor Darrell; Kate Saenko (J. Mach. Learn. Res., 2016)

Adversarial Discriminative Domain Adaptation. - Eric Tzeng; Judy Hoffman; Kate Saenko; Trevor Darrell (CVPR, 2017)

Fine-Grained Recognition in the Wild: A Multi-task Domain Adaptation Approach. - Timnit Gebru; Judy Hoffman; Li Fei-Fei 001 (ICCV, 2017)

Inferring and Executing Programs for Visual Reasoning. - Justin Johnson 001; Bharath Hariharan; Laurens van der Maaten; Judy Hoffman; Li Fei-Fei 001; C. Lawrence Zitnick; Ross B. Girshick (ICCV, 2017)

Adversarial Discriminative Domain Adaptation (workshop extended abstract). - Eric Tzeng; Judy Hoffman; Kate Saenko; Trevor Darrell (ICLR (Workshop), 2017)

Label Efficient Learning of Transferable Representations acrosss Domains and Tasks. - Zelun Luo; Yuliang Zou; Judy Hoffman; Li Fei-Fei 001 (NIPS, 2017)

VisDA: The Visual Domain Adaptation Challenge. - Xingchao Peng; Ben Usman; Neela Kaushik; Judy Hoffman; Dequan Wang; Kate Saenko (CoRR, 2017)

Multiple-Source Adaptation for Regression Problems. - Judy Hoffman; Mehryar Mohri; Ningshan Zhang (CoRR, 2017)

Label Efficient Learning of Transferable Representations across Domains and Tasks. - Zelun Luo; Yuliang Zou; Judy Hoffman; Li Fei-Fei 001 (CoRR, 2017)

Simultaneous Deep Transfer Across Domains and Tasks. - Judy Hoffman; Eric Tzeng; Trevor Darrell; Kate Saenko (Domain Adaptation in Computer Vision Applications, 2017)

VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation. - Xingchao Peng; Ben Usman; Neela Kaushik; Dequan Wang; Judy Hoffman; Kate Saenko (CVPR Workshops, 2018)

Adapting to Continuously Shifting Domains. - Andreea Bobu; Eric Tzeng; Judy Hoffman; Trevor Darrell (ICLR (Workshop), 2018)

CyCADA: Cycle-Consistent Adversarial Domain Adaptation. - Judy Hoffman; Eric Tzeng; Taesung Park; Jun-Yan Zhu; Phillip Isola; Kate Saenko; Alexei A. Efros; Trevor Darrell (ICML, 2018)

Algorithms and Theory for Multiple-Source Adaptation. - Judy Hoffman; Mehryar Mohri; Ningshan Zhang (NeurIPS, 2018)

Scaling Human-Object Interaction Recognition Through Zero-Shot Learning. - Liyue Shen; Serena Yeung; Judy Hoffman; Greg Mori; Li Fei-Fei 001 (WACV, 2018)

Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation. - Xingchao Peng; Ben Usman; Kuniaki Saito; Neela Kaushik; Judy Hoffman; Kate Saenko (CoRR, 2018)

SplitNet: Sim2Sim and Task2Task Transfer for Embodied Visual Navigation. - Daniel Gordon; Abhishek Kadian; Devi Parikh; Judy Hoffman; Dhruv Batra (ICCV, 2019)

Predictive Inequity in Object Detection. - Benjamin Wilson; Judy Hoffman; Jamie Morgenstern (CoRR, 2019)

Robust Learning with Jacobian Regularization. - Judy Hoffman; Daniel A. Roberts; Sho Yaida (CoRR, 2019)

Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets. - Yogesh Balaji; Tom Goldstein; Judy Hoffman (CoRR, 2019)

Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents. - Samyak Datta; Oleksandr Maksymets; Judy Hoffman; Stefan Lee; Dhruv Batra; Devi Parikh (CoRL, 2020)

TIDE: A General Toolbox for Identifying Object Detection Errors. - Daniel Bolya; Sean Foley; James Hays; Judy Hoffman (ECCV (3), 2020)

Learning to Balance Specificity and Invariance for In and Out of Domain Generalization. - Prithvijit Chattopadhyay; Yogesh Balaji; Judy Hoffman (ECCV (9), 2020)

Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses. - Fu Lin; Rohit Mittapalli; Prithvijit Chattopadhyay; Daniel Bolya; Judy Hoffman (ECCV Workshops (1), 2020)

Masked reconstruction based self-supervision for human activity recognition. - Harish Haresamudram; Apoorva Beedu; Varun Agrawal; Patrick L. Grady; Irfan A. Essa; Judy Hoffman; Thomas Plötz (ISWC, 2020)

Auxiliary Task Reweighting for Minimum-data Learning. - Baifeng Shi; Judy Hoffman; Kate Saenko; Trevor Darrell; Huijuan Xu 001 (NeurIPS, 2020)

Analyzing Visual Representations in Embodied Navigation Tasks. - Erik Wijmans; Julian Straub; Dhruv Batra; Irfan Essa; Judy Hoffman; Ari Morcos (CoRR, 2020)

UDIS: Unsupervised Discovery of Bias in Deep Visual Recognition Models. - Arvindkumar Krishnakumar; Viraj Prabhu; Sruthi Sudhakar; Judy Hoffman (BMVC, 2021)

Mitigating Bias in Visual Transformers via Targeted Alignment. - Sruthi Sudhakar; Viraj Prabhu; Arvindkumar Krishnakumar; Judy Hoffman (BMVC, 2021)

RobustNav: Towards Benchmarking Robustness in Embodied Navigation. - Prithvijit Chattopadhyay; Judy Hoffman; Roozbeh Mottaghi; Aniruddha Kembhavi (ICCV, 2021)

Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings. - Viraj Prabhu; Arjun Chandrasekaran; Kate Saenko; Judy Hoffman (ICCV, 2021)

SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation. - Viraj Prabhu; Shivam Khare; Deeksha Kartik; Judy Hoffman (ICCV, 2021)

Temporal Action Detection with Multi-level Supervision. - Baifeng Shi; Qi Dai 001; Judy Hoffman; Kate Saenko; Trevor Darrell; Huijuan Xu 001 (ICCV, 2021)

Scalable Diverse Model Selection for Accessible Transfer Learning. - Daniel Bolya; Rohit Mittapalli; Judy Hoffman (NeurIPS, 2021)

Representation Learning Through Latent Canonicalizations. - Or Litany; Ari Morcos; Srinath Sridhar 002; Leonidas J. Guibas; Judy Hoffman (WACV, 2021)

Multiple-source adaptation theory and algorithms. - Ningshan Zhang; Mehryar Mohri; Judy Hoffman (Ann. Math. Artif. Intell., 2021)

S4T: Source-free domain adaptation for semantic segmentation via self-supervised selective self-training. - Viraj Prabhu; Shivam Khare; Deeksha Kartik; Judy Hoffman (CoRR, 2021)

VIsCUIT: Visual Auditor for Bias in CNN Image Classifier. - Seongmin Lee 007; Judy Hoffman; Zijie J. Wang; Duen Horng Chau (CVPR, 2022)

Can domain adaptation make object recognition work for everyone? - Viraj Prabhu; Ramprasaath R. Selvaraju; Judy Hoffman; Nikhil Naik (CVPR Workshops, 2022)

Hydra Attention: Efficient Attention with Many Heads. - Daniel Bolya; Cheng-Yang Fu; Xiaoliang Dai; Peizhao Zhang; Judy Hoffman (ECCV Workshops (7), 2022)

ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings. - Arjun Majumdar; Gunjan Aggarwal; Bhavika Devnani; Judy Hoffman; Dhruv Batra (NeurIPS, 2022)

Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency. - Viraj Prabhu; Sriram Yenamandra; Aaditya Singh; Judy Hoffman (NeurIPS, 2022)

Multiple-source adaptation theory and algorithms - addendum. - Judy Hoffman; Mehryar Mohri; Ningshan Zhang (Ann. Math. Artif. Intell., 2022)

ConceptEvo: Interpreting Concept Evolution in Deep Learning Training. - Haekyu Park; Seongmin Lee 007; Benjamin Hoover; Austin P. Wright; Omar Shaikh; Rahul Duggal; Nilaksh Das; Judy Hoffman; Duen Horng Chau (CoRR, 2022)

Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries. - Haekyu Park; Seongmin Lee 007; Benjamin Hoover; Austin P. Wright; Omar Shaikh; Rahul Duggal; Nilaksh Das; Kevin Li; Judy Hoffman; Duen Horng Chau (CIKM, 2023)

Token Merging for Fast Stable Diffusion. - Daniel Bolya; Judy Hoffman (CVPR Workshops, 2023)

Pasta: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain Generalization. - Prithvijit Chattopadhyay; Kartik Sarangmath; Vivek Vijaykumar; Judy Hoffman (ICCV, 2023)

Benchmarking Low-Shot Robustness to Natural Distribution Shifts. - Aaditya Singh; Kartik Sarangmath; Prithvijit Chattopadhyay; Judy Hoffman (ICCV, 2023)

FACTS: First Amplify Correlations and Then Slice to Discover Bias. - Sriram Yenamandra; Pratik Ramesh; Viraj Prabhu; Judy Hoffman (ICCV, 2023)

Token Merging: Your ViT But Faster. - Daniel Bolya; Cheng-Yang Fu; Xiaoliang Dai; Peizhao Zhang; Christoph Feichtenhofer; Judy Hoffman (ICLR, 2023)

Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles. - Chaitanya Ryali; Yuan-Ting Hu; Daniel Bolya; Chen Wei 005; Haoqi Fan 001; Po-Yao Huang 001; Vaibhav Aggarwal; Arkabandhu Chowdhury; Omid Poursaeed; Judy Hoffman; Jitendra Malik; Yanghao Li; et al. (ICML, 2023)

Synthetic-to-Real Domain Adaptation for Action Recognition: A Dataset and Baseline Performances. - Arun V. Reddy; Ketul Shah; William Paul; Rohita Mocharla; Judy Hoffman; Kapil D. Katyal; Dinesh Manocha; Celso M. de Melo; Rama Chellappa (ICRA, 2023)

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. - Micah Goldblum; Hossein Souri; Renkun Ni; Manli Shu; Viraj Prabhu; Gowthami Somepalli; Prithvijit Chattopadhyay; Mark Ibrahim; Adrien Bardes; Judy Hoffman; Rama Chellappa; Andrew Gordon Wilson; et al. (NeurIPS, 2023)

LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images. - Viraj Prabhu; Sriram Yenamandra; Prithvijit Chattopadhyay; Judy Hoffman (NeurIPS, 2023)

Structure-Encoding Auxiliary Tasks for Improved Visual Representation in Vision-and-Language Navigation. - Chia-Wen Kuo; Chih-Yao Ma; Judy Hoffman; Zsolt Kira (WACV, 2023)

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting. - Viraj Prabhu; David Acuna; Andrew Liao; Rafid Mahmood; Marc T. Law; Judy Hoffman; Sanja Fidler; James Lucas (CoRR, 2023)

ZipIt! Merging Models from Different Tasks without Training. - George Stoica; Daniel Bolya; Jakob Bjorner; Taylor Hearn; Judy Hoffman (CoRR, 2023)

ICON2: Reliably Benchmarking Predictive Inequity in Object Detection. - Sruthi Sudhakar; Viraj Prabhu; Olga Russakovsky; Judy Hoffman (CoRR, 2023)

Memory in Plain Sight: A Survey of the Uncanny Resemblances between Diffusion Models and Associative Memories. - Benjamin Hoover; Hendrik Strobelt; Dmitry Krotov; Judy Hoffman; Zsolt Kira; Duen Horng Chau (CoRR, 2023)

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting. - Viraj Prabhu; David Acuna; Rafid Mahmood; Marc T. Law; Yuan-Hong Liao; Judy Hoffman; Sanja Fidler; James Lucas (Trans. Mach. Learn. Res., 2023)

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives. - Kristen Grauman; Andrew Westbury; Lorenzo Torresani; Kris Kitani; Jitendra Malik; Triantafyllos Afouras; Kumar Ashutosh; Vijay Baiyya; Siddhant Bansal; Bikram Boote; Eugene Byrne; Zachary Chavis; et al. (CVPR, 2024)

SKYSCENES: A Synthetic Dataset for Aerial Scene Understanding. - Sahil Khose; Anisha Pal; Aayushi Agarwal 001; Deepanshi 002; Judy Hoffman; Prithvijit Chattopadhyay (ECCV (79), 2024)

Window Attention is Bugged: How not to Interpolate Position Embeddings. - Daniel Bolya; Chaitanya Ryali; Judy Hoffman; Christoph Feichtenhofer (ICLR, 2024)

AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images. - Prithvijit Chattopadhyay; Bharat Goyal; Boglarka Ecsedi; Viraj Prabhu; Judy Hoffman (ICLR, 2024)

ZipIt! Merging Models from Different Tasks without Training. - George Stoica; Daniel Bolya; Jakob Bjorner; Pratik Ramesh; Taylor Hearn; Judy Hoffman (ICLR, 2024)

Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors. - Anisha Pal; Julia Kruk; Mansi Phute; Manognya Bhattaram; Diyi Yang; Duen Horng Chau; Judy Hoffman (NeurIPS, 2024)

We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline. - Simar Kareer; Vivek Vijaykumar; Harsh Maheshwari; Judy Hoffman; Prithvijit Chattopadhyay; Viraj Prabhu (Trans. Mach. Learn. Res., 2024)

Gaze-LLE: Gaze Target Estimation via Large-Scale Learned Encoders. - Fiona Ryan; Ajay Bati; Sangmin Lee 001; Daniel Bolya; Judy Hoffman; James M. Rehg (CVPR, 2025)

Improving Personalized Search with Regularized Low-Rank Parameter Updates. - Fiona Ryan; Josef Sivic; Fabian Caba Heilbron; Judy Hoffman; James M. Rehg; Bryan C. Russell (CVPR, 2025)

Model merging with SVD to tie the Knots. - George Stoica; Pratik Ramesh; Boglarka Ecsedi; Leshem Choshen; Judy Hoffman (ICLR, 2025)

EgoMimic: Scaling Imitation Learning via Egocentric Video. - Simar Kareer; Dhruv Patel; Ryan Punamiya; Pranay Mathur; Shuo Cheng; Chen Wang 053; Judy Hoffman; Danfei Xu (ICRA, 2025)

Contrastive Flow Matching. - George Stoica; Vivek Ramanujan; Xiang Fan; Ali Farhadi; Ranjay Krishna; Judy Hoffman (CoRR, 2025)

EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data. - Ryan Punamiya; Dhruv Patel; Patcharapong Aphiwetsa; Pranav Kuppili; Lawrence Y. Zhu; Simar Kareer; Judy Hoffman; Danfei Xu (CoRR, 2025)