Recurrent autoregressive networks for online multi-object tracking K Fang, Y Xiang, X Li, S Savarese IEEE Winter Conference on Applications of Computer Vision (WACV), 2018 | 312 | 2018 |
Learning task-oriented grasping for tool manipulation from simulated self-supervision K Fang, Y Zhu, A Garg, A Kurenkov, V Mehta, L Fei-Fei, S Savarese Robotics: Science and Systems (RSS), 2018 | 227 | 2018 |
Scene memory transformer for embodied agents in long-horizon tasks K Fang, A Toshev, L Fei-Fei, S Savarese IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 196 | 2019 |
Delay: Robust spatial layout estimation for cluttered indoor scenes S Dasgupta, K Fang, K Chen, S Savarese IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 | 171 | 2016 |
Synergies between affordance and geometry: 6-dof grasp detection via implicit representations Z Jiang, Y Zhu, M Svetlik, K Fang, Y Zhu arXiv preprint arXiv:2104.01542, 2021 | 132 | 2021 |
Multi-task domain adaptation for deep learning of instance grasping from simulation K Fang, Y Bai, S Hinterstoisser, S Savarese, M Kalakrishnan IEEE International Conference on Robotics and Automation (ICRA), 2018 | 126 | 2018 |
Open x-embodiment: Robotic learning datasets and rt-x models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 118 | 2023 |
KETO: Learning Keypoint Representations for Tool Manipulation Z Qin, K Fang, Y Zhu, L Fei-Fei, S Savarese IEEE International Conference on Robotics and Automation (ICRA), 2020 | 100 | 2020 |
Demo2Vec: Reasoning object affordances from online videos K Fang, TL Wu, D Yang, S Savarese, JJ Lim IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 99 | 2018 |
Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation K Fang, Y Zhu, A Garg, S Savarese, L Fei-Fei Conference on Robot Learning (CoRL), 2019 | 49 | 2019 |
Machine learning methods and apparatus for robotic manipulation and that utilize multi-task domain adaptation Y Bai, K Fang, S Hinterstoisser, M Kalakrishnan US Patent 10,773,382, 2020 | 37 | 2020 |
Bridgedata v2: A dataset for robot learning at scale HR Walke, K Black, TZ Zhao, Q Vuong, C Zheng, P Hansen-Estruch, ... Conference on Robot Learning, 1723-1736, 2023 | 33 | 2023 |
Adaptive Procedural Task Generation for Hard-Exploration Problems K Fang, Y Zhu, S Savarese, L Fei-Fei International Conference on Learning Representations (ICLR), 2021 | 30 | 2021 |
Generalization with lossy affordances: Leveraging broad offline data for learning visuomotor tasks K Fang, P Yin, A Nair, HR Walke, G Yan, S Levine Conference on Robot Learning, 106-117, 2023 | 17 | 2023 |
Planning to practice: Efficient online fine-tuning by composing goals in latent space K Fang, P Yin, A Nair, S Levine 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 17 | 2022 |
Goal representations for instruction following: A semi-supervised language interface to control V Myers, AW He, K Fang, HR Walke, P Hansen-Estruch, CA Cheng, ... Conference on Robot Learning, 3894-3908, 2023 | 16 | 2023 |
Multi-stage cable routing through hierarchical imitation learning J Luo, C Xu, X Geng, G Feng, K Fang, L Tan, S Schaal, S Levine IEEE Transactions on Robotics, 2024 | 12 | 2024 |
Discovering Generalizable Skills via Automated Generation of Diverse Tasks K Fang, Y Zhu, S Savarese, L Fei-Fei Robotics: Science and Systems (RSS), 2021 | 12 | 2021 |
Moka: Open-vocabulary robotic manipulation through mark-based visual prompting F Liu, K Fang, P Abbeel, S Levine arXiv preprint arXiv:2403.03174, 2024 | 7 | 2024 |
Active Task Randomization: Learning Robust Skills via Unsupervised Generation of Diverse and Feasible Tasks K Fang, T Migimatsu, A Mandlekar, L Fei-Fei, J Bohg 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 6* | 2023 |