| Ppfnet: Global context aware local features for robust 3d point matching H Deng, T Birdal, S Ilic Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 619 | 2018 |
| 3D point capsule networks Y Zhao, T Birdal, H Deng, F Tombari Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 412 | 2019 |
| PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors H Deng, T Birdal, S Ilic Proceedings of the European Conference on Computer Vision (ECCV), 602-618, 2018 | 407 | 2018 |
| Humor: 3d human motion model for robust pose estimation D Rempe, T Birdal, A Hertzmann, J Yang, S Sridhar, LJ Guibas Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 259 | 2021 |
| Learning multiview 3d point cloud registration Z Gojcic, C Zhou, JD Wegner, LJ Guibas, T Birdal Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 187 | 2020 |
| Point Pair Features Based Object Detection and Pose Estimation Revisited T Birdal, S Ilic 3D Vision, 527-535, 2015 | 146 | 2015 |
| 3D Local Features for Direct Pairwise Registration H Deng, T Birdal, S Ilic Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019 | 131 | 2019 |
| Explaining the Ambiguity of Object Detection and 6D Pose from Visual Data F Manhardt, DM Arroyo, C Rupprecht, B Busam, T Birdal, N Navab, ... Proceedings of the IEEE International Conference on Computer Vision, 2019 | 115 | 2019 |
| Weakly supervised learning of rigid 3D scene flow Z Gojcic, O Litany, A Wieser, LJ Guibas, T Birdal Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 99 | 2021 |
| Quaternion equivariant capsule networks for 3d point clouds Y Zhao, T Birdal, JE Lenssen, E Menegatti, L Guibas, F Tombari European conference on computer vision, 1-19, 2020 | 93 | 2020 |
| Caspr: Learning canonical spatiotemporal point cloud representations D Rempe, T Birdal, Y Zhao, Z Gojcic, S Sridhar, LJ Guibas Advances in neural information processing systems 33, 13688-13701, 2020 | 75 | 2020 |
| Intrinsic dimension, persistent homology and generalization in neural networks T Birdal, A Lou, LJ Guibas, U Simsekli Advances in Neural Information Processing Systems 34, 6776-6789, 2021 | 52 | 2021 |
| Survey of Higher Order Rigid Body Motion Interpolation Methods for Keyframe Animation and Continuous-Time Trajectory Estimation A Haarbach, T Birdal, S Ilic International Conference on 3D Vision, 381--389, 2018 | 50 | 2018 |
| MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization J Huang, H Wang, T Birdal, M Sung, F Arrigoni, SM Hu, L Guibas arXiv preprint arXiv:2101.06605, 2021 | 48 | 2021 |
| Deep bingham networks: Dealing with uncertainty and ambiguity in pose estimation H Deng, M Bui, N Navab, L Guibas, S Ilic, T Birdal International Journal of Computer Vision 130 (7), 1627-1654, 2022 | 45 | 2022 |
| Deformation-aware 3d model embedding and retrieval MA Uy, J Huang, M Sung, T Birdal, L Guibas Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 45 | 2020 |
| Point2cyl: Reverse engineering 3d objects from point clouds to extrusion cylinders MA Uy, YY Chang, M Sung, P Goel, JG Lambourne, T Birdal, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 41 | 2022 |
| Quantum permutation synchronization T Birdal, V Golyanik, C Theobalt, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 41 | 2021 |
| Bayesian pose graph optimization via bingham distributions and tempered geodesic mcmc T Birdal, U Şimşekli, MO Eken, S Ilic Advances in Neural Information Processing Systems 31 31, 308--319, 2018 | 40 | 2018 |
| Topological Deep Learning: Going Beyond Graph Data M Hajij, G Zamzmi, T Papamarkou, N Miolane, A Guzmán-Sáenz, ... arXiv preprint arXiv:2206.00606, 2023 | 36* | 2023 |
Leonidas GuibasProfessor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
