| Pointnet++: Deep hierarchical feature learning on point sets in a metric space CR Qi, L Yi, H Su, LJ Guibas arXiv preprint arXiv:1706.02413, 2017 | 2298 | 2017 |
| 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 | 1730 | 2015 |
| A scalable active framework for region annotation in 3d shape collections L Yi, VG Kim, D Ceylan, IC Shen, M Yan, H Su, C Lu, Q Huang, A Sheffer, ... ACM Transactions on Graphics (ToG) 35 (6), 1-12, 2016 | 343 | 2016 |
| Syncspeccnn: Synchronized spectral cnn for 3d shape segmentation L Yi, H Su, X Guo, LJ Guibas Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 288 | 2017 |
| Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding K Mo, S Zhu, AX Chang, L Yi, S Tripathi, LJ Guibas, H Su Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 126 | 2019 |
| Gspn: Generative shape proposal network for 3d instance segmentation in point cloud L Yi, W Zhao, H Wang, M Sung, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 89 | 2019 |
| Structurenet: Hierarchical graph networks for 3d shape generation K Mo, P Guerrero, L Yi, H Su, P Wonka, N Mitra, LJ Guibas arXiv preprint arXiv:1908.00575, 2019 | 53 | 2019 |
| Large-scale 3d shape reconstruction and segmentation from shapenet core55 L Yi, L Shao, M Savva, H Huang, Y Zhou, Q Wang, B Graham, M Engelcke, ... arXiv preprint arXiv:1710.06104, 2017 | 40 | 2017 |
| Texturenet: Consistent local parametrizations for learning from high-resolution signals on meshes J Huang, H Zhang, L Yi, T Funkhouser, M Nießner, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 38 | 2019 |
| 3D-assisted feature synthesis for novel views of an object H Su, F Wang, E Yi, LJ Guibas Proceedings of the IEEE International Conference on Computer Vision, 2677-2685, 2015 | 37 | 2015 |
| Learning hierarchical shape segmentation and labeling from online repositories L Yi, L Guibas, A Hertzmann, VG Kim, H Su, E Yumer arXiv preprint arXiv:1705.01661, 2017 | 33 | 2017 |
| Supervised fitting of geometric primitives to 3d point clouds L Li, M Sung, A Dubrovina, L Yi, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 31 | 2019 |
| Image super-resolution via analysis sparse prior Q Ning, K Chen, L Yi, C Fan, Y Lu, J Wen IEEE Signal Processing Letters 20 (4), 399-402, 2013 | 30 | 2013 |
| Sapien: A simulated part-based interactive environment F Xiang, Y Qin, K Mo, Y Xia, H Zhu, F Liu, M Liu, H Jiang, Y Yuan, H Wang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 21 | 2020 |
| Geonet: Deep geodesic networks for point cloud analysis T He, H Huang, L Yi, Y Zhou, C Wu, J Wang, S Soatto Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 19 | 2019 |
| Deep part induction from articulated object pairs L Yi, H Huang, D Liu, E Kalogerakis, H Su, L Guibas arXiv preprint arXiv:1809.07417, 2018 | 19 | 2018 |
| Beyond holistic object recognition: Enriching image understanding with part states C Lu, H Su, Y Li, Y Lu, L Yi, CK Tang, LJ Guibas Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 18 | 2018 |
| Category-level articulated object pose estimation X Li, H Wang, L Yi, LJ Guibas, AL Abbott, S Song Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 16 | 2020 |
| StructEdit: Learning structural shape variations K Mo, P Guerrero, L Yi, H Su, P Wonka, NJ Mitra, LJ Guibas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 8 | 2020 |
| Cosegnet: Deep co-segmentation of 3d shapes with group consistency loss C Zhu, K Xu, S Chaudhuri, L Yi, L Guibas, H Zhang arXiv preprint arXiv:1903.10297, 2019 | 6 | 2019 |
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVahvistettu sähköpostiosoite verkkotunnuksessa cs.stanford.edu
