| TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers X Bai, Z Hu, X Zhu, Q Huang, Y Chen, H Fu, CL Tai CVPR 2022, 2022 | 667 | 2022 |
| FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection T Wang, X Zhu, J Pang, D Lin International Conference on Computer Vision Workshops (ICCVW), 2021 | 626 | 2021 |
| 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 CVPR 2021 (Oral), 2021 | 604 | 2021 |
| TrafficPredict: Trajectory prediction for heterogeneous traffic-agents Y Ma*, X Zhu*, S Zhang, R Yang, W Wang, D Manocha AAAI 2019, 2019 | 524 | 2019 |
| Adapting object detectors via selective cross-domain alignment X Zhu, J Pang, C Yang, J Shi, D Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 413 | 2019 |
| Probabilistic and geometric depth: Detecting objects in perspective T Wang, X Zhu, J Pang, D Lin Conference on Robot Learning (CoRL), 2021 | 287 | 2021 |
| Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints Y Xu, X Zhu, J Shi, G Zhang, H Bao, H Li ICCV 2019, 2019 | 268 | 2019 |
| Cylinder3d: An effective 3d framework for driving-scene lidar semantic segmentation H Zhou, X Zhu, X Song, Y Ma, Z Wang, H Li, D Lin arXiv preprint arXiv:2008.01550, 2020 | 207 | 2020 |
| Point-to-voxel knowledge distillation for lidar semantic segmentation Y Hou, X Zhu, Y Ma, CC Loy, Y Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 190 | 2022 |
| Pose Guided Human Video Generation C Yang, Z Wang, X Zhu, C Huang, J Shi, D Lin European Conference on Computer Vision (ECCV) 2018, 2018 | 158 | 2018 |
| CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP R Chen, Y Liu, L Kong, X Zhu, Y Ma, Y Li, Y Hou, Y Qiao, W Wang CVPR 2023, 2023 | 136 | 2023 |
| Rethinking range view representation for lidar segmentation L Kong, Y Liu, R Chen, Y Ma, X Zhu, Y Li, Y Hou, Y Qiao, Z Liu ICCV 2023, 2023 | 135 | 2023 |
| SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds X Zhu, Y Ma, T Wang, Y Xu, J Shi, D Lin European Conference on Computer Vision (ECCV) 2020, 2020 | 135 | 2020 |
| Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation X Zhu, H Zhou, C Yang, J Shi, D Lin European Conference on Computer Vision (ECCV) 2018, 2018 | 134 | 2018 |
| Dependency Exploitation: A Unified CNN-RNN Approach for Visual Emotion Recognition X Zhu, L Li, W Zhang, T Rao, M Xu, Q Huang, D Xu Proceedings of the Internal Joint Conference on Artificial Intelligence …, 2017 | 122 | 2017 |
| Vision-centric bev perception: A survey Y Ma, T Wang, X Bai, H Yang, Y Hou, Y Wang, Y Qiao, R Yang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024, 2024 | 121 | 2024 |
| LiDAR-based Panoptic Segmentation via Dynamic Shifting Network F Hong, H Zhou, X Zhu, H Li, Z Liu CVPR 2021, 2021 | 118 | 2021 |
| 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 44 (10), 6807 …, 2021 | 108 | 2021 |
| Lif-seg: Lidar and camera image fusion for 3d lidar semantic segmentation L Zhao, H Zhou, X Zhu, X Song, H Li, W Tao IEEE Transactions on Multimedia, 2021 | 86 | 2021 |
| Not all areas are equal: Transfer learning for semantic segmentation via hierarchical region selection R Sun*, X Zhu*, C Wu, C Huang, J Shi, L Ma Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 86 | 2019 |
Yuexin MaAssistant Professor, School of Information Science and Technology, ShanghaiTech University在 shanghaitech.edu.cn 的电子邮件经过验证
