| PointRCNN: 3d object proposal generation and detection from point cloud S Shi, X Wang, H Li The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770-779, 2019 | 1040 | 2019 |
| PV-RCNN: Point-voxel feature set abstraction for 3d object detection S Shi, C Guo, L Jiang, Z Wang, J Shi, X Wang, H Li The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 10529 …, 2020 | 550 | 2020 |
| From points to parts: 3d object detection from point cloud with part-aware and part-aggregation network S Shi, Z Wang, J Shi, X Wang, H Li IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020, 2020 | 349* | 2020 |
| FP-DNN: An automated framework for mapping deep neural networks onto FPGAs with RTL-HLS hybrid templates Y Guan, H Liang, N Xu, W Wang, S Shi, X Chen, G Sun, W Zhang, J Cong IEEE 25th Annual International Symposium on Field-Programmable Custom …, 2017 | 267 | 2017 |
| PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation L Jiang, H Zhao, S Shi, S Liu, CW Fu, J Jia The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4867-4876, 2020 | 118 | 2020 |
| Gal: Geometric adversarial loss for single-view 3d-object reconstruction L Jiang, S Shi, X Qi, J Jia Proceedings of the European conference on computer vision (ECCV), 802-816, 2018 | 89 | 2018 |
| Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection J Deng, S Shi, P Li, W Zhou, Y Zhang, H Li AAAI Conference on Artificial Intelligence (AAAI), 2020 | 87 | 2020 |
| PV-RCNN++: Point-voxel feature set abstraction with local vector representation for 3D object detection S Shi, L Jiang, J Deng, Z Wang, C Guo, J Shi, X Wang, H Li arXiv preprint arXiv:2102.00463, 2021 | 43 | 2021 |
| ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection J Yang*, S Shi*, Z Wang, H Li, X Qi The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 10368 …, 2021 | 32 | 2021 |
| SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud H Yi, S Shi, M Ding, J Sun, K Xu, H Zhou, Z Wang, S Li, G Wang IEEE International Conference on Robotics and Automation (ICRA), 2020, 2020 | 28 | 2020 |
| OpenPCDet: An open-source toolbox for 3d object detection from point clouds OD Team https://github.com/open-mmlab/OpenPCDet, 2020 | 27 | 2020 |
| Liga-stereo: Learning lidar geometry aware representations for stereo-based 3d detector X Guo, S Shi, X Wang, H Li International Conference on Computer Vision (ICCV), 3153-3163, 2021 | 19 | 2021 |
| Back-tracing representative points for voting-based 3d object detection in point clouds B Cheng, L Sheng, S Shi, M Yang, D Xu The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 8963-8972, 2021 | 18 | 2021 |
| Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentation L Jiang, S Shi, Z Tian, X Lai, S Liu, CW Fu, J Jia International Conference on Computer Vision (ICCV), 6423-6432, 2021 | 11 | 2021 |
| Feature Intertwiner for Object Detection H Li, B Dai, S Shi, W Ouyang, X Wang International Conference on Learning Representation (ICLR), 2019, 2019 | 11 | 2019 |
| PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection/3D Tracking/Domain Adaptation of Waymo Open Dataset Challenges S Shi, C Guo, J Yang, H Li Technical report for Waymo Open Dataset Challenges at Workshop of CVPR 2020 …, 2020 | 7 | 2020 |
| St3d++: Denoised self-training for unsupervised domain adaptation on 3d object detection J Yang, S Shi, Z Wang, H Li, X Qi arXiv preprint arXiv:2108.06682, 2021 | 3 | 2021 |
| Towards Efficient 3D Object Detection with Knowledge Distillation J Yang, S Shi, R Ding, Z Wang, X Qi arXiv preprint arXiv:2205.15156, 2022 | | 2022 |
| MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection X Chen, S Shi, B Zhu, KC Cheung, H Xu, H Li arXiv preprint arXiv:2205.05979, 2022 | | 2022 |
| RBGNet: Ray-based Grouping for 3D Object Detection H Wang, S Shi, Z Yang, R Fang, Q Qian, H Li, B Schiele, L Wang CVPR 2022, 2022 | | 2022 |
Hongsheng Li (李鸿升)Associate Professor at The Chinese University of Hong Kong在 ee.cuhk.edu.hk 的电子邮件经过验证
