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Qingyong Hu
Qingyong Hu
Other names胡庆拥
Ph.D. of Computer Science, University of Oxford
Verified email at cs.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
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
17542020
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
15722020
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
3192019
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
2492020
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
2392020
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
2322022
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
1632020
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
1292021
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
1062021
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
592021
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
542022
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
512022
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, 2023
282023
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
252019
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
242017
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
232023
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
202021
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
192022
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
182022
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
182021
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