| 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 | 1811 | 2017 |
| Pointnet++: Deep hierarchical feature learning on point sets in a metric space CR Qi, L Yi, H Su, LJ Guibas Advances in neural information processing systems, 5099-5108, 2017 | 1041 | 2017 |
| Volumetric and multi-view cnns for object classification on 3d data CR Qi, H Su, M Nießner, A Dai, M Yan, LJ Guibas Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 616 | 2016 |
| 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 | 454 | 2015 |
| Frustum pointnets for 3d object detection from rgb-d data CR Qi, W Liu, C Wu, H Su, LJ Guibas Proc. Computer Vision and Pattern Recognition (CVPR), IEEE, 2018 | 370 | 2018 |
| Shape completion using 3d-encoder-predictor cnns and shape synthesis A Dai, C Ruizhongtai Qi, M Nießner Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 148 | 2017 |
| Fpnn: Field probing neural networks for 3d data Y Li, S Pirk, H Su, CR Qi, LJ Guibas Advances in Neural Information Processing Systems, 307-315, 2016 | 137 | 2016 |
| Joint embeddings of shapes and images via cnn image purification Y Li, H Su, CR Qi, N Fish, D Cohen-Or, LJ Guibas ACM transactions on graphics (TOG) 34 (6), 1-12, 2015 | 115 | 2015 |
| Kpconv: Flexible and deformable convolution for point clouds H Thomas, CR Qi, JE Deschaud, B Marcotegui, F Goulette, LJ Guibas Proceedings of the IEEE International Conference on Computer Vision, 6411-6420, 2019 | 23 | 2019 |
| Deep hough voting for 3d object detection in point clouds CR Qi, O Litany, K He, LJ Guibas Proceedings of the IEEE International Conference on Computer Vision, 9277-9286, 2019 | 22 | 2019 |
| Generating 3d adversarial point clouds C Xiang, CR Qi, B Li Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 17 | 2019 |
| Exploring hidden dimensions in parallelizing convolutional neural networks Z Jia, S Lin, CR Qi, A Aiken arXiv preprint arXiv:1802.04924, 2018 | 16 | 2018 |
| FlowNet3D: Learning Scene Flow in 3D Point Clouds X Liu, CR Qi, LJ Guibas arXiv preprint arXiv:1806.01411, 2019 | 15 | 2019 |
| Teaching digital signal processing with Stanford's Lab-in-a-Box FA Mujica, WJ Esposito, A Gonzalez, CR Qi, C Vassos, M Wieman, ... 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE …, 2015 | 10 | 2015 |
| Order-Aware Generative Modeling Using the 3D-Craft Dataset Z Chen, D Guo, T Xiao, S Xie, X Chen, H Yu, J Gray, K Srinet, H Fan, J Ma, ... Proceedings of the IEEE International Conference on Computer Vision, 1764-1773, 2019 | | 2019 |
Leonidas GuibasProfessor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
