| ImageNet Large Scale Visual Recognition Challenge O Russakovsky, J Deng, H Su, J Krause, S Satheesh, S Ma, Z Huang, ... IJCV, 2014 | 22935 | 2014 |
| Pointnet: Deep learning on point sets for 3d classification and segmentation CR Qi, H Su, K Mo, LJ Guibas Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 4355 | 2017 |
| 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 | 2719 | 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 | 1891 | 2015 |
| Object bank: A high-level image representation for scene classification & semantic feature sparsification H Su, LJ Li, L Fei-Fei, EP Xing Advances in neural information processing systems, 1378-1386, 2010 | 1245* | 2010 |
| Volumetric and multi-view cnns for object classification on 3d data H Su, CR Qi, M Nießner, A Dai, M Yan, LJ Guibas Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 1070 | 2016 |
| Frustum pointnets for 3d object detection from rgb-d data CR Qi, W Liu, C Wu, H Su, LJ Guibas CVPR, 2018 | 939 | 2018 |
| A point set generation network for 3d object reconstruction from a single image H Fan, H Su, LJ Guibas Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 836 | 2017 |
| Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views H Su, CR Qi, Y Li, LJ Guibas Proceedings of the IEEE International Conference on Computer Vision, 2686-2694, 2015 | 652 | 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 | 394 | 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 | 311 | 2017 |
| Fpnn: Field probing neural networks for 3d data Y Li, S Pirk, H Su, CR Qi, LJ Guibas arXiv preprint arXiv:1605.06240, 2016 | 228 | 2016 |
| Synthesizing training images for boosting human 3d pose estimation W Chen, H Wang, Y Li, H Su, Z Wang, C Tu, D Lischinski, D Cohen-Or, ... 2016 Fourth International Conference on 3D Vision (3DV), 479-488, 2016 | 219 | 2016 |
| Objectnet3d: A large scale database for 3d object recognition Y Xiang, W Kim, W Chen, J Ji, C Choy, H Su, R Mottaghi, L Guibas, ... European conference on computer vision, 160-176, 2016 | 214 | 2016 |
| Crowdsourcing annotations for visual object detection H Su, J Deng, L Fei-Fei Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012 | 210 | 2012 |
| Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories H Su, M Sun, L Fei-Fei, S Savarese 2009 IEEE 12th International Conference on Computer Vision, 213-220, 2009 | 204 | 2009 |
| Objects as attributes for scene classification H Su, LJ Li, Y Lim, L Fei-Fei Trends and Topics in Computer Vision, 57-69, 2012 | 186* | 2012 |
| Joint embeddings of shapes and images via cnn image purification H Su, Y Li, CR Qi, N Fish, D Cohen-Or, LJ Guibas ACM Transactions on Graphics (TOG) 34 (6), 234, 2015 | 158 | 2015 |
| A multi-view probabilistic model for 3d object classes H Su, M Sun, S Savarese, L Fei-Fei Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on …, 2009 | 153 | 2009 |
| 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 CVPR 2019, 2018 | 152 | 2018 |
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
