About Me
I obtained my Ph.D. degree from City University of Hong Kong (2020~2024) under the supervision of Prof. Junhui Hou, during which I was also fortunate to work closely with Prof. Wenping Wang and Prof. Ying He. Previously, I worked as a short-term research intern guided by Prof. Runmin Cong. I received my B.Sc. degree from Beijing Normal University in 2019.
Since August 2024, I joined Tencent as a senior researcher, leading an effort to 3D Generative Models and AI for Games.
News
- [2023.09] Two papers, NeuroGF for geodesics learning, UPIDet for cross-modal 3D detection, got accepted by NeurIPS-2023.
- [2023.12] One paper, Cross-PCC for image-assisted 3D point cloud completion, got accepted by TMM.
- [2023.12] One paper, PointVST for self-supervised 3D point cloud backbone pre-training, got accepted by TVCG.
- [2024.06] One paper, SPCV for spatio-temporal structurization of dynamic 3D point cloud sequences, got accepted by TPAMI.
- [2024.09] One paper, Flatten Anything Model for surface parameterization (UV unwrapping), got accepted by NeurIPS-2024.
- [2025.03] One paper, Human as Points for single-image 3D human reconstruction, got accepted by TPAMI.
- [2025.10] One paper, HuGDiffusion for 3D human Gaussian diffusion, got accepted by TVCG.
- [2025.10] One paper, FlexPara for flexible multi-chart surface parameterization, got accepted by TPAMI.
Research
Current Research Focuses
3D generative models have achieved impressive advances in recent times; however, their actual applicability in professional asset creation workflows still remains insufficient. I am currently concentrating my research efforts on [Game-Ready] 3D AIGC and its integration into the asset production pipelines of real-world game industry. Ongoing R&D projects include:
- Ultra-Realistic and Physically-Consistent Mesh Detail Generation. (See our earlier results in SuperCarver.)
- Mesh Texture Super-Resolution and Controllable Repainting.
- Practical Mesh UV Unwrapping. (See our earlier results in FAM, FlexPara.)
Ph.D. Research Topics
I have broad interests in developing deep learning models and neural optimization algorithms to solve various geometry, vision, and graphics problems. My Ph.D. research primarily falls within the areas of 3D Spatial Intelligence and 2D-3D Cross-Modal Learning, including the following specific topics and projects:
- Geometry Modeling and Surface Computing:
- Regular Representation (Flattening-Net, RegGeoNet)
- 4D Point Cloud Video Spatio-Temporal Structurization (SPCV)
- Mesh Parameterization (FAM)
- Neural Geodesics (NeuroGF)
- Point Cloud Processing and Reconstruction:
- Sampling (MOPS-Net)
- Completion (Cross-PCC)
- Generation (WarpingGAN)
- 4D Point Cloud Video Interpolation (IDEA-Net)
- Visual-Geometric Joint Learning:
- 3D Digital Human:
- Reconstruction & Novel View Synthesis (HaP, HuGDiffusion)
Services
Conference Reviewer: NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, ACM MM, IJCAI, CVM, etc.
Journal Reviewer: TIP, TVCG, TMM, TCSVT, TITS, TGRS, JSTARS, etc.
Selected Publications
![]() | Yingzhi Tang, Qijian Zhang, Junhui Hou Pre-print |
![]() | Qijian Zhang, Xiaozheng Jian, Xuan Zhang, Wenping Wang, Junhui Hou Pre-print |




















