| Mvsnet: Depth inference for unstructured multi-view stereo Y Yao, Z Luo, S Li, T Fang, L Quan Proceedings of the European conference on computer vision (ECCV), 767-783, 2018 | 1218 | 2018 |
| Recurrent mvsnet for high-resolution multi-view stereo depth inference Y Yao, Z Luo, S Li, T Shen, T Fang, L Quan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 558 | 2019 |
| Blendedmvs: A large-scale dataset for generalized multi-view stereo networks Y Yao, Z Luo, S Li, J Zhang, Y Ren, L Zhou, T Fang, L Quan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 364 | 2020 |
| Aslfeat: Learning local features of accurate shape and localization Z Luo, L Zhou, X Bai, H Chen, J Zhang, Y Yao, S Li, T Fang, L Quan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 296 | 2020 |
| Contextdesc: Local descriptor augmentation with cross-modality context Z Luo, T Shen, L Zhou, J Zhang, Y Yao, S Li, T Fang, L Quan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 274 | 2019 |
| Geodesc: Learning local descriptors by integrating geometry constraints Z Luo, T Shen, L Zhou, S Zhu, R Zhang, Y Yao, T Fang, L Quan Proceedings of the European conference on computer vision (ECCV), 168-183, 2018 | 206 | 2018 |
| Visibility-aware Multi-view Stereo Network J Zhang, Y Yao, S Li, Z Luo, T Fang The 31st British Machine Vision Virtual Conference, BMVC 2020, 2020 | 148 | 2020 |
| Learning signed distance field for multi-view surface reconstruction J Zhang, Y Yao, L Quan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 84 | 2021 |
| Kfnet: Learning temporal camera relocalization using kalman filtering L Zhou, Z Luo, T Shen, J Zhang, M Zhen, Y Yao, T Fang, L Quan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 84 | 2020 |
| Vis-mvsnet: Visibility-aware multi-view stereo network J Zhang, S Li, Z Luo, T Fang, Y Yao International Journal of Computer Vision 131 (1), 199-214, 2023 | 44 | 2023 |
| Neilf: Neural incident light field for physically-based material estimation Y Yao, J Zhang, J Liu, Y Qu, T Fang, D McKinnon, Y Tsin, L Quan European Conference on Computer Vision, 700-716, 2022 | 44 | 2022 |
| Critical regularizations for neural surface reconstruction in the wild J Zhang, Y Yao, S Li, T Fang, D McKinnon, Y Tsin, L Quan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 33 | 2022 |
| Reconstructing thin structures of manifold surfaces by integrating spatial curves S Li, Y Yao, T Fang, L Quan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 29 | 2018 |
| Gaussian-flow: 4d reconstruction with dynamic 3d gaussian particle Y Lin, Z Dai, S Zhu, Y Yao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 22 | 2024 |
| Relightable 3d gaussian: Real-time point cloud relighting with brdf decomposition and ray tracing J Gao, C Gu, Y Lin, H Zhu, X Cao, L Zhang, Y Yao arXiv preprint arXiv:2311.16043, 2023 | 21 | 2023 |
| Consistent4d: Consistent 360 {\deg} dynamic object generation from monocular video Y Jiang, L Zhang, J Gao, W Hu, Y Yao arXiv preprint arXiv:2311.02848, 2023 | 20 | 2023 |
| Relative camera refinement for accurate dense reconstruction Y Yao, S Li, S Zhu, H Deng, T Fang, L Quan 2017 International Conference on 3D Vision (3DV), 185-194, 2017 | 20 | 2017 |
| Neilf++: Inter-reflectable light fields for geometry and material estimation J Zhang, Y Yao, S Li, J Liu, T Fang, D McKinnon, Y Tsin, L Quan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 19 | 2023 |
| Avatarbooth: High-quality and customizable 3d human avatar generation Y Zeng, Y Lu, X Ji, Y Yao, H Zhu, X Cao arXiv preprint arXiv:2306.09864, 2023 | 17 | 2023 |
| Cross-atlas convolution for parameterization invariant learning on textured mesh surface S Li, Z Luo, M Zhen, Y Yao, T Shen, T Fang, L Quan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 17 | 2019 |
Long QUANProfessor, Department of Computer Science and Engineering, HKUST在 cse.ust.hk 的电子邮件经过验证
