| Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions? A Das*, H Agrawal*, CL Zitnick, D Parikh, D Batra Empirical Methods in Natural Language Processing (EMNLP) 2016, 2016 | 565 | 2016 |
| nocaps: novel object captioning at scale H Agrawal*, K Desai*, Y Wang, X Chen, R Jain, M Johnson, D Batra, ... International Conference on Computer Vision, 8948-8957, 2019 | 379 | 2019 |
| Spatially aware multimodal transformers for textvqa Y Kant, D Batra, P Anderson, A Schwing, D Parikh, J Lu, H Agrawal European Conference on Computer Vision, 715-732, 2020 | 103 | 2020 |
| Object-proposal evaluation protocol is' gameable' N Chavali*, H Agrawal*, A Mahendru*, D Batra Computer Vision and Pattern Recognition (CVPR) 2016, 835-844, 2016 | 100 | 2016 |
| Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning J Aneja*, H Agrawal*, D Batra, A Schwing International Conference on Computer Vision (ICCV), 2019 | 81 | 2019 |
| Sort Story: Sorting Jumbled Images and Captions into Stories H Agrawal*, A Chandrasekaran*, D Batra, D Parikh, M Bansal Empirical Methods in Natural Language Processing (EMNLP) 2016, 2016 | 78 | 2016 |
| Housekeep: Tidying virtual households using commonsense reasoning Y Kant, A Ramachandran, S Yenamandra, I Gilitschenski, D Batra, A Szot, ... European Conference on Computer Vision, 355-373, 2022 | 76 | 2022 |
| Large language models as generalizable policies for embodied tasks A Szot, M Schwarzer, H Agrawal, B Mazoure, R Metcalf, W Talbott, ... The Twelfth International Conference on Learning Representations, 2023 | 63 | 2023 |
| SOAT: A Scene-and Object-Aware Transformer for Vision-and-Language Navigation A Moudgil, A Majumdar, H Agrawal, S Lee, D Batra Advances in Neural Information Processing Systems 34, 2021 | 61 | 2021 |
| 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 | 54 | 2019 |
| Cloudcv: Large-scale distributed computer vision as a cloud service H Agrawal, CS Mathialagan, Y Goyal, N Chavali, P Banik, A Mohapatra, ... Mobile Cloud Visual Media Computing: From Interaction to Service, 265-290, 2015 | 54 | 2015 |
| The Surprising Effectiveness of Visual Odometry Techniques for Embodied PointGoal Navigation X Zhao, H Agrawal, D Batra, AG Schwing Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 50 | 2021 |
| Contrast and classify: Training robust vqa models Y Kant, A Moudgil, D Batra, D Parikh, H Agrawal Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 35 | 2021 |
| Simple and Effective Synthesis of Indoor 3D Scenes JY Koh, H Agrawal, D Batra, R Tucker, A Waters, H Lee, Y Yang, ... arXiv preprint arXiv:2204.02960, 2022 | 17 | 2022 |
| Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms Z Li, K You, H Zhang, D Feng, H Agrawal, X Li, MPS Moorthy, J Nichols, ... arXiv preprint arXiv:2410.18967, 2024 | 12 | 2024 |
| CloudCV: Deep Learning and Computer Vision on the Cloud H Agrawal Virginia Tech, 2016 | 11 | 2016 |
| Grounding Multimodal Large Language Models in Actions A Szot, B Mazoure, H Agrawal, D Hjelm, Z Kira, A Toshev arXiv preprint arXiv:2406.07904, 2024 | 9 | 2024 |
| Fabrik: An Online Collaborative Neural Network Editor U Garg, V Prabhu, D Yadav, R Ramrakhya, H Agrawal, D Batra arXiv preprint arXiv:1810.11649, 2018 | 6 | 2018 |
| Known unknowns: Learning novel concepts using reasoning-by-elimination H Agrawal, EA Meirom, Y Atzmon, S Mannor, G Chechik Uncertainty in Artificial Intelligence, 2021 | 4 | 2021 |
| From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons A Szot, B Mazoure, O Attia, A Timofeev, H Agrawal, D Hjelm, Z Gan, Z Kira, ... arXiv preprint arXiv:2412.08442, 2024 | | 2024 |
Dhruv BatraPrev: FAIR (Meta AI), Georgia TechE-mailová adresa ověřena na: dhruvbatra.com
