| Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation X Zhu*, H Zhou*, T Wang, F Hong, Y Ma, W Li, H Li, D Lin IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021, 2020 | 72 | 2020 |
| SSN: Shape Signature Networks for Multi-class Object Detection from Point Cloud X Zhu, Y Ma, T Wang, Y Xu, J Shi, D Lin European Conference on Computer Vision (ECCV) 2020, 2020 | 36 | 2020 |
| FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection T Wang, X Zhu, J Pang, D Lin IEEE/CVF International Conference on Computer Vision (ICCV) Workshops 2021, 2021 | 34 | 2021 |
| MMDetection3D: OpenMMLab next-generation platform for general 3D object detection. M Contributors https://github.com/open-mmlab/mmdetection3d, 2020 | 30 | 2020 |
| Probabilistic and Geometric Depth: Detecting Objects in Perspective T Wang, X Zhu, J Pang, D Lin Conference on Robot Learning (CoRL) 2021, 2021 | 20 | 2021 |
| Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds T Wang, X Zhu, D Lin Conference on Robot Learning (CoRL) 2020, 2020 | 17 | 2020 |
| Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception X Zhu, H Zhou, T Wang, F Hong, W Li, Y Ma, H Li, R Yang, D Lin IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 | 7 | 2021 |
| Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion T Wu, L Pan, J Zhang, T Wang, Z Liu, D Lin Conference on Neural Information Processing Systems (NeurIPS), 2021 | 4 | 2021 |
| SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimation X Peng, X Zhu, T Wang, Y Ma IEEE Winter Conference on Applications of Computer Vision (WACV) 2022, 2021 | 2 | 2021 |
| FLAVA: Find, Localize, Adjust and Verify to Annotate LiDAR-based Point Clouds T Wang, C He, Z Wang, J Shi, D Lin ACM Symposium on User Interface Software and Technology (UIST) 2020, Poster, 2020 | 1 | 2020 |
Dahua LinThe Chinese University of Hong KongVerified email at ie.cuhk.edu.hk
