| View synthesis by appearance flow T Zhou, S Tulsiani, W Sun, J Malik, AA Efros Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 795 | 2016 |
| Learning category-specific mesh reconstruction from image collections A Kanazawa, S Tulsiani, AA Efros, J Malik Proceedings of the European Conference on Computer Vision (ECCV), 371-386, 2018 | 664 | 2018 |
| Multi-view supervision for single-view reconstruction via differentiable ray consistency S Tulsiani, T Zhou, AA Efros, J Malik Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 620 | 2017 |
| Viewpoints and keypoints S Tulsiani, J Malik IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, 2015 | 531 | 2015 |
| Learning category-specific deformable 3D models for object reconstruction S Tulsiani, A Kar, J Carreira, J Malik IEEE transactions on pattern analysis and machine intelligence 39 (4), 719-731, 2017 | 482* | 2017 |
| Hierarchical Surface Prediction for 3D Object Reconstruction C Häne, S Tulsiani, J Malik International Conference on 3D Vision (3DV), 2017 | 387 | 2017 |
| Learning Shape Abstractions by Assembling Volumetric Primitives S Tulsiani, H Su, LJ Guibas, AA Efros, J Malik Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 380 | 2017 |
| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 279 | 2023 |
| Multi-view consistency as supervisory signal for learning shape and pose prediction S Tulsiani, AA Efros, J Malik Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 226 | 2018 |
| Autosdf: Shape priors for 3d completion, reconstruction and generation P Mittal, YC Cheng, M Singh, S Tulsiani Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 208 | 2022 |
| Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction Z Zhou, S Tulsiani Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 185 | 2023 |
| Where2act: From pixels to actions for articulated 3d objects K Mo, LJ Guibas, M Mukadam, A Gupta, S Tulsiani Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 170 | 2021 |
| Layer-structured 3d scene inference via view synthesis S Tulsiani, R Tucker, N Snavely Proceedings of the European Conference on Computer Vision (ECCV), 302-317, 2018 | 168 | 2018 |
| Ners: Neural reflectance surfaces for sparse-view 3d reconstruction in the wild J Zhang, G Yang, S Tulsiani, D Ramanan Advances in Neural Information Processing Systems 34, 29835-29847, 2021 | 150 | 2021 |
| Factoring shape, pose, and layout from the 2d image of a 3d scene S Tulsiani, S Gupta, DF Fouhey, AA Efros, J Malik Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 149 | 2018 |
| Canonical Surface Mapping via Geometric Cycle Consistency N Kulkarni, A Gupta, S Tulsiani IEEE International Conference on Computer Vision (ICCV), 2019, 2019 | 114 | 2019 |
| Articulation-aware canonical surface mapping N Kulkarni, A Gupta, DF Fouhey, S Tulsiani Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 105 | 2020 |
| Visual imitation made easy S Young, D Gandhi, S Tulsiani, A Gupta, P Abbeel, L Pinto Conference on Robot Learning, 1992-2005, 2021 | 103 | 2021 |
| Learning unsupervised multi-view stereopsis via robust photometric consistency T Khot, S Agrawal, S Tulsiani, C Mertz, S Lucey, M Hebert arXiv preprint arXiv:1905.02706, 2019 | 99 | 2019 |
| Compositional Video Prediction Y Ye, M Singh, A Gupta, S Tulsiani IEEE International Conference on Computer Vision (ICCV), 2019, 2019 | 96 | 2019 |
Abhinav GuptaProfessor, Robotics Institute, Carnegie Mellon University在 cs.cmu.edu 的電子郵件地址已通過驗證