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Li Xianzhi Associate professor Supervisor of Master's Candidates Phone: 17302700905 Email: xzli@hust.edu.cn Academic Areas: 3D vision, computer graphics, deep learning |
Personal Profile
I am an associate professor at Huazhong University of Science and Technology (HUST). My research interests include 3D vision, computer graphics, point cloud processing, and deep learning. I am dedicated to designing machine learning algorithms for processing, analyzing, and sensing 3D data.
Before joining HUST, I was a post-doctoral fellow at The Chinese University of Hong Kong (CUHK) and Hong Kong Center for Logistics Robotics. I have received my Ph.D. degree from the Department of Computer Science and Engineering, CUHK, supervised by Prof. Pheng-Ann Heng and Prof. Chi-Wing Fu. Before that, I received the M.Sc. at CUHK in 2015 and B. Eng. at Sichuan University in 2014.
For more details, please also visit my personal website: https://nini-lxz.github.io/
Academic Degrees
2016.8 - 2020.7
Ph.D., Computer Science and Engineering, CUHK
2014.8 - 2015.7
M. Sc., Biomedical Engineering, CUHK
2010.8 - 2014.7
B. Eng., Biomedical Engineering, Sichuan University
Professional Experience
2021.11 - Now
Huazhong University of Science and Technology - School of Computer Science and Technology- Associate Professor
2020.8 - 2021.8
The Chinese University of Hong Kong - Computer Science and Engineering - Postdoctoral Researcher
Courses Taught
[1] 2022-Now Spring Computer Vision
[2] 2018-2019 Spring CSCI 5210 Advanced Topics in Computer Graphics and Visualization
[3] 2017-2018 Fall CSCI3260 Principles of Computer Graphics
[4] 2017-2018 Spring CSCI2100 Data Structure
[5] 2016-2017 Fall CSCI3260 Principles of Computer Graphics
Awards and Honors
[6] Teaching Assistant of Merit, 2018
[7] Biomedical Engineering Scholarship, 2015
[8] Outstanding Graduates of Sichuan University, 2014
[9] National Scholarship in China, 2013
Selected Projects Funded
Principal Investigator: “Research on Indoor Scene 3D Reconstruction and Understanding using Limited Labeled Training Data” funded by National Natural Science Foundation of China (2023.01-2025.12)
Selected Publications
[1] Xu J, Li X*, Tang Y, Yu Q, et al. CasFusionNet: A cascaded network for point cloud semantic scene completion by dense feature fusion [C]//Association for the Advancement of Artificial Intelligence (AAAI), 2023. (* Corresponding Author)
[2] Li X, Cao R, Feng Y, et al. A sim-to-real object recognition and localization framework for industrial robotic bin picking [J]. IEEE Robotics and Automation Letters (RA-L), 2022, 7(2): 3961-3968.
[3] Feng Y, Yang B, Li X*, et al. Towards robust part-aware instance segmentation for industrial bin picking [C]//IEEE International Conference on Robotics and Automation (ICRA), 2022. (* Corresponding Author)
[4] Li X, Li R, Chen G, et al. A rotation-invariant framework for deep point cloud analysis [J]. IEEE Transactions on Visualization and Computer Graphics (TVCG), 2021.
[5] Li X, Yu L, Fu C W, et al. Unsupervised detection of distinctive regions on 3D shapes [J]. ACM Transactions on Graphics (TOG), 2020, 39(5): 1-14.
[6] Li X, Li R, Zhu L, et al. DNF-Net: a deep normal filtering network for mesh denoising [J]. IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020, 27(10): 4060-4072.
[7] Yu Y, Li X*, and Liu F. E-DBPN: Enhanced deep back-projection networks for remote sensing scene image superresolution [J]. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2020, 58(8): 5503-5515. (* Corresponding Author)
[8] Li R, Li X*, Heng P A, et al. Point cloud upsampling via disentangled refinement [C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021: 344-353. (* Corresponding Author)
[9] Li X, Zhu L, Fu C W, et al. Non-local low-rank normal filtering for mesh denoising [J]. Computer Graphics Forum, 2018, 37(7), 155-166.
[10] Yu L*, Li X*, Fu C W, et al. PU-Net: Point cloud upsampling network [C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2018: 2790-2799. (* Joint First Author)
[11] Yu L*, Li X*, Fu C W, et al. EC-Net: an edge-aware point set consolidation network [C]//Proceedings of the European Conference on Computer Vision (ECCV). 2018: 386-402. (* Joint First Author)
Professional Affiliations
Research Group
Embedded and Pervasive Computing Lab
Enrollment Information
[1] Computer Science and Technology/CST (Computer Software and Theory)/2023
[2] School of Computer Science and Technology/CST (Computer Software and Theory)/2023
Personal Homepage
Web:/hust/mu_faculty/lixianzhi1/en/index.htm