Scholar
Tianjia Shao
Google Scholar ID: WdZjfzQAAAAJ
University of Leeds
Citations & Impact
Citations
1,961
H-index
25
i10-index
37
Publications
20
Co-authors
0
Contact
Publications
Resume
Academic Achievements
- Publications in 2025:
- - CVPR 2025: High-fidelity 3D Object Generation from Single Image with RGBN-Volume Gaussian Reconstruction Model
- - CVPR 2025: Real-time High-fidelity Gaussian Human Avatars with Position-based Interpolation of Spatially Distributed MLPs
- - CVPR 2025: EnliveningGS: Active Locomotion of 3DGS
- - CVPR 2025: Gaussian Splashing: Unified Particles for Versatile Motion Synthesis and Rendering
- - AAAI 2025: GenesisTex2: Stable, Consistent and High-Quality Text-to-Texture Generation
- - IEEE TVCG 2025: Relightable Detailed Human Reconstruction from Sparse Flashlight Images
- - FCS 2025: Animatable 3D Gaussians for modeling dynamic humans
- Publications in 2024:
- - SIGGRAPH Asia 2024: CPoser: An Optimization-after-Parsing Approach for Text-to-Pose Generation Using Large Language Models
- - SIGGRAPH 2024: RTG-SLAM: Real-time 3D Reconstruction at Scale using Gaussian Splatting
- Served as a Technical Papers Committee member for ACM SIGGRAPH 2023 and 2022; Associate Editor for The Visual Computer; Program Co-Chair for Computational Visual Media 2022.
Research Experience
- Assistant Researcher at the State Key Laboratory of CAD&CG, Zhejiang University; Lecturer in the School of Computing, University of Leeds, UK; ZJU100 Young Professor in the State Key Laboratory of CAD&CG, Zhejiang University.
Education
- Ph.D. in Computer Science from the Institute for Advanced Study, Tsinghua University, under the guidance of Prof. Baining Guo; B.S. from the Department of Automation, Tsinghua University; Visiting Researcher at University College London, working with Prof. Niloy Mitra; Research Intern at Microsoft Research Asia for four years.
Background
- Research Interests: Acquisition, reconstruction, and generation of 3D contents in Computer Graphics and Computer Vision. Recent research includes 3D scene reconstruction (real-time dense SLAM, offline high-quality reconstruction, autonomous reconstruction with robots), digital human creation, and 3D AIGC.
Miscellany
- Looking for strongly-motivated PhD and Master students to join his research team. Interested students in computer graphics and computer vision can contact him.