| 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 | 11364 | 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 30, 2017 | 7808 | 2017 |
| 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 | 2154 | 2018 |
| Kpconv: Flexible and deformable convolution for point clouds H Thomas, CR Qi, JE Deschaud, B Marcotegui, F Goulette, LJ Guibas Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 1669 | 2019 |
| 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 | 1663 | 2016 |
| Deep hough voting for 3d object detection in point clouds CR Qi, O Litany, K He, LJ Guibas proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 882 | 2019 |
| 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 | 848 | 2015 |
| 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 | 557 | 2017 |
| FlowNet3D: Learning Scene Flow in 3D Point Clouds X Liu, CR Qi, LJ Guibas arXiv preprint arXiv:1806.01411, 2019 | 356 | 2019 |
| Pointcontrast: Unsupervised pre-training for 3d point cloud understanding S Xie, J Gu, D Guo, CR Qi, L Guibas, O Litany Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 326 | 2020 |
| 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 | 309 | 2016 |
| Generating 3d adversarial point clouds C Xiang, CR Qi, B Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 215 | 2019 |
| Imvotenet: Boosting 3d object detection in point clouds with image votes CR Qi, X Chen, O Litany, LJ Guibas Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 214 | 2020 |
| 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 | 190 | 2015 |
| Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset S Ettinger, S Cheng, B Caine, C Liu, H Zhao, S Pradhan, Y Chai, B Sapp, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 177 | 2021 |
| Pointnet++: Deep hierarchical feature learning on point sets in a metric space. arXiv 2017 CR Qi, L Yi, H Su, LJ Guibas arXiv preprint arXiv:1706.02413, 0 | 111 | |
| Exploring Hidden Dimensions in Parallelizing Convolutional Neural Networks. Z Jia, S Lin, CR Qi, A Aiken ICML, 2279-2288, 2018 | 104 | 2018 |
| Offboard 3d object detection from point cloud sequences CR Qi, Y Zhou, M Najibi, P Sun, K Vo, B Deng, D Anguelov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 96 | 2021 |
| Spg: Unsupervised domain adaptation for 3d object detection via semantic point generation Q Xu, Y Zhou, W Wang, CR Qi, D Anguelov Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 90 | 2021 |
| Exploring hidden dimensions in accelerating convolutional neural networks Z Jia, S Lin, CR Qi, A Aiken International Conference on Machine Learning, 2274-2283, 2018 | 32 | 2018 |
Leonidas GuibasProfessor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
