| 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 | 1310 | 2020 |
| 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 | 1308 | 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 | 1182 | 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 | 264 | 2019 |
| 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 | 159 | 2020 |
| 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 | 153 | 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 | 126 | 2022 |
| 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 | 108 | 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 | 84 | 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 | 60 | 2021 |
| 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 | 35 | 2022 |
| 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 | 31 | 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 | 21 | 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 | 21 | 2017 |
| 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 | 18 | 2022 |
| Correlation Filter Tracking: Beyond an Open-loop System Q Hu, Y Guo, Y Chen, J Xiao, W An British Machine Vision Conference (BMVC), 152.1-152.12, 2017 | 13 | 2017 |
| 三维视觉前沿进展 龙霄潇， 程新景， 朱昊， 张朋举， 刘浩敏， 李俊， 郑林涛， 胡庆拥， 刘浩， ... 中国图象图形学报, 2021 | 12 | 2021 |
| 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 | 11 | 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 | 11 | 2021 |
| Semi-online multiple object tracking using graphical tracklet association J Wang, Y Guo, X Tang, Q Hu, W An IEEE Signal Processing Letters (IEEE SPL) 25 (11), 1725-1729, 2018 | 10 | 2018 |
Yulan GuoSenior Member of IEEE & ACMПодтвержден адрес электронной почты в домене nudt.edu.cn
