3d shapenets: A deep representation for volumetric shapes Z Wu, S Song, A Khosla, F Yu, L Zhang, X Tang, J Xiao Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 7098 | 2015 |
Shapenet: An information-rich 3d model repository AX Chang, T Funkhouser, L Guibas, P Hanrahan, Q Huang, Z Li, ... arXiv preprint arXiv:1512.03012, 2015 | 6055 | 2015 |
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop F Yu, A Seff, Y Zhang, S Song, T Funkhouser, J Xiao arXiv preprint arXiv:1506.03365, 2015 | 2519 | 2015 |
Sun rgb-d: A rgb-d scene understanding benchmark suite S Song, SP Lichtenberg, J Xiao Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 2247 | 2015 |
Matterport3d: Learning from rgb-d data in indoor environments A Chang, A Dai, T Funkhouser, M Halber, M Niessner, M Savva, S Song, ... International Conference on 3D Vision (3DV), 2017 | 2038 | 2017 |
Semantic scene completion from a single depth image S Song, F Yu, A Zeng, AX Chang, M Savva, T Funkhouser Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1418 | 2017 |
3dmatch: Learning local geometric descriptors from rgb-d reconstructions A Zeng, S Song, M Nießner, M Fisher, J Xiao, T Funkhouser Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1171 | 2017 |
Deep sliding shapes for amodal 3d object detection in rgb-d images S Song, J Xiao Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 861 | 2016 |
Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching A Zeng, S Song, KT Yu, E Donlon, FR Hogan, M Bauza, D Ma, O Taylor, ... The International Journal of Robotics Research 41 (7), 690-705, 2022 | 793 | 2022 |
Normalized object coordinate space for category-level 6d object pose and size estimation H Wang, S Sridhar, J Huang, J Valentin, S Song, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 779 | 2019 |
Learning synergies between pushing and grasping with self-supervised deep reinforcement learning A Zeng, S Song, S Welker, J Lee, A Rodriguez, T Funkhouser 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 680 | 2018 |
Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge A Zeng, KT Yu, S Song, D Suo, E Walker, A Rodriguez, J Xiao 2017 IEEE international conference on robotics and automation (ICRA), 1386-1383, 2017 | 574 | 2017 |
Sliding shapes for 3d object detection in depth images S Song, J Xiao Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 551 | 2014 |
Diffusion policy: Visuomotor policy learning via action diffusion C Chi, Z Xu, S Feng, E Cousineau, Y Du, B Burchfiel, R Tedrake, S Song The International Journal of Robotics Research, 02783649241273668, 2023 | 465 | 2023 |
TossingBot: Learning to Throw Arbitrary Objects with Residual Physics A Zeng, S Song, J Lee, A Rodriguez, T Funkhouser Robotics: Science and Systems (RSS), 2019 | 456 | 2019 |
Tracking revisited using RGBD camera: Unified benchmark and baselines S Song, J Xiao Proceedings of the IEEE international conference on computer vision, 233-240, 2013 | 364 | 2013 |
Datacomp: In search of the next generation of multimodal datasets SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ... Advances in Neural Information Processing Systems 36, 2024 | 319 | 2024 |
Physically-based rendering for indoor scene understanding using convolutional neural networks Y Zhang, S Song, E Yumer, M Savva, JY Lee, H Jin, T Funkhouser Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 318 | 2017 |
Neural illumination: Lighting prediction for indoor environments S Song, T Funkhouser Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 308 | 2019 |
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 | 301* | 2023 |