| Sparse fuse dense: Towards high quality 3d detection with depth completion X Wu, L Peng, H Yang, L Xie, C Huang, C Deng, H Liu, D Cai Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 144 | 2022 |
| Graph r-cnn: Towards accurate 3d object detection with semantic-decorated local graph H Yang, Z Liu, X Wu, W Wang, W Qian, X He, D Cai European Conference on Computer Vision, 662-679, 2022 | 62 | 2022 |
| GD-MAE: generative decoder for MAE pre-training on lidar point clouds H Yang, T He, J Liu, H Chen, B Wu, B Lin, X He, W Ouyang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 40 | 2023 |
| Ponder: Point cloud pre-training via neural rendering D Huang, S Peng, T He, H Yang, X Zhou, W Ouyang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 18 | 2023 |
| Pvt-ssd: Single-stage 3d object detector with point-voxel transformer H Yang, W Wang, M Chen, B Lin, T He, H Chen, X He, W Ouyang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 14 | 2023 |
| Ponderv2: Pave the way for 3d foundataion model with a universal pre-training paradigm H Zhu, H Yang, X Wu, D Huang, S Zhang, X He, T He, H Zhao, C Shen, ... arXiv preprint arXiv:2310.08586, 2023 | 12 | 2023 |
| 3d-queryis: A query-based framework for 3d instance segmentation J Liu, T He, H Yang, R Su, J Tian, J Wu, H Guo, K Xu, W Ouyang arXiv preprint arXiv:2211.09375, 2022 | 12 | 2022 |
| Unipad: A universal pre-training paradigm for autonomous driving H Yang, S Zhang, D Huang, X Wu, H Zhu, T He, S Tang, H Zhao, Q Qiu, ... arXiv preprint arXiv:2310.08370, 2023 | 10 | 2023 |
| SparsePoint: Fully End-to-End Sparse 3D Object Detector Z Liu, G Xu, H Yang, M Chen, K Wu, Z Yang, H Liu, D Cai arXiv preprint arXiv:2103.10042, 2021 | 10* | 2021 |
| MCS: Multi-Target Masked Point Modeling with Learnable Codebook and Siamese Decoders Q Qiu, H Yang, W Wang, S Zhang, H Gao, H Ying, W Hua, X He arXiv preprint arXiv:2309.13235, 2023 | | 2023 |
