| Learning to balance specificity and invariance for in and out of domain generalization P Chattopadhyay, Y Balaji, J Hoffman Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 210 | 2020 |
| Counting everyday objects in everyday scenes P Chattopadhyay, R Vedantam, RR Selvaraju, D Batra, D Parikh Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 184 | 2017 |
| Do explanations make VQA models more predictable to a human? A Chandrasekaran, V Prabhu, D Yadav, P Chattopadhyay, D Parikh arXiv preprint arXiv:1810.12366, 2018 | 108 | 2018 |
| Evaluating visual conversational agents via cooperative human-ai games P Chattopadhyay, D Yadav, V Prabhu, A Chandrasekaran, A Das, S Lee, ... Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 5 …, 2017 | 91 | 2017 |
| It takes two to tango: Towards theory of AI's mind A Chandrasekaran, D Yadav, P Chattopadhyay, V Prabhu, D Parikh arXiv preprint arXiv:1704.00717, 2017 | 75 | 2017 |
| Choose your neuron: Incorporating domain knowledge through neuron-importance RR Selvaraju, P Chattopadhyay, M Elhoseiny, T Sharma, D Batra, ... Proceedings of the European conference on computer vision (ECCV), 526-541, 2018 | 50 | 2018 |
| Evalai: Towards better evaluation systems for ai agents D Yadav, R Jain, H Agrawal, P Chattopadhyay, T Singh, A Jain, SB Singh, ... arXiv preprint arXiv:1902.03570, 2019 | 48 | 2019 |
| Robustnav: Towards benchmarking robustness in embodied navigation P Chattopadhyay, J Hoffman, R Mottaghi, A Kembhavi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 45 | 2021 |
| Improving generative visual dialog by answering diverse questions V Murahari, P Chattopadhyay, D Batra, D Parikh, A Das arXiv preprint arXiv:1909.10470, 2019 | 38 | 2019 |
| Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks M Goldblum, H Souri, R Ni, M Shu, V Prabhu, G Somepalli, ... Advances in Neural Information Processing Systems 36, 2024 | 34 | 2024 |
| Lance: Stress-testing visual models by generating language-guided counterfactual images V Prabhu, S Yenamandra, P Chattopadhyay, J Hoffman Advances in Neural Information Processing Systems 36, 25165-25184, 2023 | 18 | 2023 |
| Pasta: Proportional amplitude spectrum training augmentation for syn-to-real domain generalization P Chattopadhyay, K Sarangmath, V Vijaykumar, J Hoffman Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 7 | 2023 |
| IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL N Modhe, P Chattopadhyay, M Sharma, A Das, D Parikh, D Batra, ... | 5* | 2020 |
| Benchmarking Low-Shot Robustness to Natural Distribution Shifts A Singh, K Sarangmath, P Chattopadhyay, J Hoffman Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
| We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline S Kareer, V Vijaykumar, H Maheshwari, P Chattopadhyay, J Hoffman, ... arXiv preprint arXiv:2402.00868, 2024 | 2 | 2024 |
| Likelihood landscapes: A unifying principle behind many adversarial defenses F Lin, R Mittapalli, P Chattopadhyay, D Bolya, J Hoffman Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 2 | 2020 |
| AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images P Chattopadhyay, B Goyal, B Ecsedi, V Prabhu, J Hoffman International Conference on Learning Representations, 2024 | | 2024 |
| SkyScenes: A Synthetic Dataset for Aerial Scene Understanding S Khose, A Pal, A Agarwal, J Hoffman, P Chattopadhyay arXiv preprint arXiv:2312.06719, 2023 | | 2023 |
| Augmentation Curriculum Learning For Generalization in RL D Yung, A Szot, P Chattopadhyay, J Hoffman, Z Kira | | |
| Exploring Weak-Supervision and Generative Models for Semantic Segmentation P Chattopadhyay, R Selvaraju, V Prabhu | | |
Devi ParikhPreviously: FAIR and GenAI @ Meta. Georgia TechVerified email at gatech.edu
