| Deep learning for 3d point clouds: A survey Y Guo*, H Wang*, Q Hu*, H Liu*, L Liu, M Bennamoun IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2020 | 2095 | 2020 |
| RandLA-Net: Efficient semantic segmentation of large-scale point clouds Q Hu, B Yang, L Xie, S Rosa, Y Guo, Z Wang, N Trigoni, A Markham IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), 2020 | 1889 | 2020 |
| Learning object bounding boxes for 3d instance segmentation on point clouds B Yang, J Wang, R Clark, Q Hu, S Wang, A Markham, N Trigoni Advances in Neural Information Processing Systems (NeurIPS 2019), 6737-6746, 2019 | 369 | 2019 |
| Axiom-based grad-cam: Towards accurate visualization and explanation of cnns R Fu, Q Hu, X Dong, Y Guo, Y Gao, B Li BMVC 2020, 2020 | 332 | 2020 |
| Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds Y Zhang, Q Hu*, G Xu, Y Ma, J Wan, Y Guo IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2022), 2022 | 325 | 2022 |
| SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration S Ao*, Q Hu*, B Yang, A Markham, Y Guo IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), 2020 | 318 | 2020 |
| Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges Q Hu, B Yang, S Khalid, W Xiao, N Trigoni, A Markham IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), 2020 | 196 | 2020 |
| Learning semantic segmentation of large-scale point clouds with random sampling Q Hu, B Yang, L Xie, S Rosa, Y Guo, Z Wang, N Trigoni, A Markham IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8338 …, 2021 | 187 | 2021 |
| Sqn: Weakly-supervised semantic segmentation of large-scale 3d point clouds Q Hu, B Yang, G Fang, Y Guo, A Leonardis, N Trigoni, A Markham European Conference on Computer Vision (ECCV 2022), 2021 | 151 | 2021 |
| Detecting and tracking small and dense moving objects in satellite videos: A benchmark Q Yin, Q Hu, H Liu, F Zhang, Y Wang, Z Lin, W An, Y Guo IEEE Transactions on Geoscience and Remote Sensing 60, 1-18, 2021 | 99 | 2021 |
| STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset M Chen, Q Hu*, T Hugues, A Feng, Y Hou, K McCullough, L Soibelman arXiv preprint arXiv:2203.09065, 2022 | 78 | 2022 |
| Sensaturban: Learning semantics from urban-scale photogrammetric point clouds Q Hu, B Yang, S Khalid, W Xiao, N Trigoni, A Markham International Journal of Computer Vision 130 (2), 316-343, 2022 | 76 | 2022 |
| RoReg: Pairwise point cloud registration with oriented descriptors and local rotations H Wang, Y Liu, Q Hu, B Wang, J Chen, Z Dong, Y Guo, W Wang, B Yang IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (8), 10376 …, 2023 | 65 | 2023 |
| Buffer: Balancing accuracy, efficiency, and generalizability in point cloud registration S Ao, Q Hu, H Wang, K Xu, Y Guo Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 55 | 2023 |
| 3DAC: Learning Attribute Compression for Point Clouds G Fang, Q Hu, H Wang, Y Xu, Y Guo IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2022), 2022 | 33 | 2022 |
| Devnet: Self-supervised monocular depth learning via density volume construction K Zhou, L Hong, C Chen, H Xu, C Ye, Q Hu, Z Li ECCV 2022, 125-142, 2022 | 31 | 2022 |
| Continuous mapping convolution for large-scale point clouds semantic segmentation K Yan, Q Hu, H Wang, X Huang, L Li, S Ji IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021 | 26 | 2021 |
| Robust long-term tracking via instance specific proposals H Liu, Q Hu, B Li, Y Guo IEEE Transactions on Instrumentation and Measurement (IEEE TIM), 2019 | 25 | 2019 |
| Object tracking using multiple features and adaptive model updating Q Hu, Y Guo, Z Lin, W An, H Cheng IEEE Transactions on Instrumentation and Measurement 66 (11), 2882-2897, 2017 | 25 | 2017 |
| No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces JX Zhong, K Zhou, Q Hu*, B Wang, N Trigoni, A Markham IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2022), 2022 | 23 | 2022 |
Yulan GuoProfessor, Sun Yat-sen UniversityVerified email at sysu.edu.cn
