| Pu-net: Point cloud upsampling network L Yu, X Li, CW Fu, D Cohen-Or, PA Heng Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 739 | 2018 |
| Pu-gan: a point cloud upsampling adversarial network R Li, X Li, CW Fu, D Cohen-Or, PA Heng Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 509 | 2019 |
| Ec-net: an edge-aware point set consolidation network L Yu, X Li, CW Fu, D Cohen-Or, PA Heng Proceedings of the European conference on computer vision (ECCV), 386-402, 2018 | 322 | 2018 |
| Pointaugment: an auto-augmentation framework for point cloud classification R Li, X Li, PA Heng, CW Fu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 216 | 2020 |
| Point cloud upsampling via disentangled refinement R Li, X Li, PA Heng, CW Fu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 156 | 2021 |
| Deep floor plan recognition using a multi-task network with room-boundary-guided attention Z Zeng, X Li, YK Yu, CW Fu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 149 | 2019 |
| SP-GAN: Sphere-guided 3D shape generation and manipulation R Li, X Li, KH Hui, CW Fu ACM Transactions on Graphics (TOG) 40 (4), 1-12, 2021 | 146 | 2021 |
| A rotation-invariant framework for deep point cloud analysis X Li, R Li, G Chen, CW Fu, D Cohen-Or, PA Heng IEEE transactions on visualization and computer graphics 28 (12), 4503-4514, 2021 | 120 | 2021 |
| Point-bind & point-llm: Aligning point cloud with multi-modality for 3d understanding, generation, and instruction following Z Guo, R Zhang, X Zhu, Y Tang, X Ma, J Han, K Chen, P Gao, X Li, H Li, ... arXiv preprint arXiv:2309.00615, 2023 | 114 | 2023 |
| Attention GANs: Unsupervised deep feature learning for aerial scene classification Y Yu, X Li, F Liu IEEE Transactions on Geoscience and Remote Sensing 58 (1), 519-531, 2019 | 112 | 2019 |
| DNF-Net: A deep normal filtering network for mesh denoising X Li, R Li, L Zhu, CW Fu, PA Heng IEEE Transactions on Visualization and Computer Graphics 27 (10), 4060-4072, 2020 | 59 | 2020 |
| Repcd-net: Feature-aware recurrent point cloud denoising network H Chen, Z Wei, X Li, Y Xu, M Wei, J Wang International Journal of Computer Vision 130 (3), 615-629, 2022 | 58 | 2022 |
| Joint-mae: 2d-3d joint masked autoencoders for 3d point cloud pre-training Z Guo, R Zhang, L Qiu, X Li, PA Heng arXiv preprint arXiv:2302.14007, 2023 | 52 | 2023 |
| Non‐local low‐rank normal filtering for mesh denoising X Li, L Zhu, CW Fu, PA Heng Computer Graphics Forum 37 (7), 155-166, 2018 | 48 | 2018 |
| A sim-to-real object recognition and localization framework for industrial robotic bin picking X Li, R Cao, Y Feng, K Chen, B Yang, CW Fu, Y Li, Q Dou, YH Liu, ... IEEE Robotics and Automation Letters 7 (2), 3961-3968, 2022 | 46 | 2022 |
| Data fusion for intelligent crowd monitoring and management systems: A survey X Li, Q Yu, B Alzahrani, A Barnawi, A Alhindi, D Alghazzawi, Y Miao IEEE Access 9, 47069-47083, 2021 | 35 | 2021 |
| E-DBPN: Enhanced deep back-projection networks for remote sensing scene image superresolution Y Yu, X Li, F Liu IEEE Transactions on Geoscience and Remote Sensing 58 (8), 5503-5515, 2020 | 30 | 2020 |
| Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model X Han, Y Tang, Z Wang, X Li Proceedings of the 32nd ACM International Conference on Multimedia, 4995-5004, 2024 | 19 | 2024 |
| Unsupervised detection of distinctive regions on 3D shapes X Li, L Yu, CW Fu, D Cohen-Or, PA Heng ACM Transactions on Graphics (TOG) 39 (5), 1-14, 2020 | 18 | 2020 |
| Attention-based depth distillation with 3d-aware positional encoding for monocular 3d object detection Z Wu, Y Wu, J Pu, X Li, X Wang Proceedings of the AAAI conference on artificial intelligence 37 (3), 2892-2900, 2023 | 17 | 2023 |
Chi-Wing Fu, PhilipThe Chinese University of Hong KongPotvrđena adresa e-pošte na cse.cuhk.edu.hk