| Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning Y Zhu, R Mottaghi, E Kolve, JJ Lim, A Gupta, L Fei-Fei, A Farhadi arXiv preprint arXiv:1609.05143, 2016 | 1937 | 2016 |
| The Role of Context for Object Detection and Semantic Segmentation in the Wild R Mottaghi, X Chen, X Liu, NG Cho, SW Lee, S Fidler, R Urtasun, A Yuille | 1750* | |
| Beyond pascal: A benchmark for 3D object detection in the wild Y Xiang, R Mottaghi, S Savarese IEEE Winter Conference on Applications of Computer Vision (WACV), 2014 | 977 | 2014 |
| OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge K Marino, M Rastegari, A Farhadi, R Mottaghi Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 962 | 2019 |
| AI2-THOR: An Interactive 3D Environment for Visual AI E Kolve, R Mottaghi, D Gordon, Y Zhu, A Gupta, A Farhadi arXiv preprint arXiv:1712.05474, 2017 | 944 | 2017 |
| ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks M Shridhar, J Thomason, D Gordon, Y Bisk, W Han, R Mottaghi, ... arXiv preprint arXiv:1912.01734, 2019 | 788 | 2019 |
| On Evaluation of Embodied Navigation Agents P Anderson, A Chang, DS Chaplot, A Dosovitskiy, S Gupta, V Koltun, ... arXiv preprint arXiv:1807.06757, 2018 | 777 | 2018 |
| Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts X Chen, R Mottaghi, X Liu, S Fidler, R Urtasun, A Yuille | 733* | |
| Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks J Lu, C Clark, R Zellers, R Mottaghi, A Kembhavi arXiv preprint arXiv:2206.08916, 2022 | 383 | 2022 |
| A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge D Schwenk, A Khandelwal, C Clark, K Marino, R Mottaghi arXiv preprint arXiv:2206.01718, 2022 | 374 | 2022 |
| ObjectNet3D: A Large Scale Database for 3D Object Recognition Y Xiang, W Kim, W Chen, J Ji, C Choy, H Su, R Mottaghi, L Guibas, ... European Conference on Computer Vision, 160-176, 2016 | 359 | 2016 |
| Visual Semantic Navigation using Scene Priors W Yang, X Wang, A Farhadi, A Gupta, R Mottaghi arXiv preprint arXiv:1810.06543, 2018 | 355 | 2018 |
| RoboTHOR: An Open Simulation-to-Real Embodied AI Platform M Deitke, W Han, A Herrasti, A Kembhavi, E Kolve, R Mottaghi, J Salvador, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 269 | 2020 |
| Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning M Wortsman, K Ehsani, M Rastegari, A Farhadi, R Mottaghi arXiv preprint arXiv:1812.00971, 2018 | 251 | 2018 |
| Simple but Effective: CLIP Embeddings for Embodied AI A Khandelwal, L Weihs, R Mottaghi, A Kembhavi arXiv preprint arXiv:2111.09888, 2021 | 230 | 2021 |
| ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects D Batra, A Gokaslan, A Kembhavi, O Maksymets, R Mottaghi, M Savva, ... arXiv preprint arXiv:2006.13171, 2020 | 227 | 2020 |
| Rearrangement: A Challenge for Embodied AI D Batra, AX Chang, S Chernova, AJ Davison, J Deng, V Koltun, S Levine, ... arXiv preprint arXiv:2011.01975, 2020 | 213 | 2020 |
| SeGAN: Segmenting and Generating the Invisible K Ehsani, R Mottaghi, A Farhadi arXiv preprint arXiv:1703.10239, 2017 | 204 | 2017 |
| ProcTHOR: Large-Scale Embodied AI Using Procedural Generation M Deitke, E VanderBilt, A Herrasti, L Weihs, J Salvador, K Ehsani, W Han, ... arXiv preprint arXiv:2206.06994, 2022 | 194* | 2022 |
| Bottom-up segmentation for top-down detection S Fidler, R Mottaghi, A Yuille, R Urtasun Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on …, 2013 | 194 | 2013 |
