| Name: | Haoxuan Li |
|---|---|
| Position: | Ph.D Candidate |
| E-Mail: | haoxuan.li@tum.de |
| Phone: | TBD |
| Room No: | 02.07.034 |
Bio
Haoxuan Li is a Ph.D. candidate at TUM Visual Computing Group, advised by Prof. Dr. Matthias Niessner. Before this, he received his Master's degree at the Technical University of Munich and his Bachelor's degree at the Shanghai Jiao Tong University.Research Interest
3D reconstruction, 3D generationPublications
2025
| MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing |
|---|
| Haoxuan Li, Ziya Erkoç, Lei Li, Daniele Sirigatti, Vladislav Rosov, Angela Dai, Matthias Nießner |
| ICCV 2025 |
| MeshPad is a generative system for creating and editing 3D triangle meshes from sketch inputs. Designed for interactive workflows, it allows users to iteratively delete and add mesh parts through simple sketch edits. MeshPad uses a Transformer-based triangle sequence model with fast speculative prediction, achieving significantly better accuracy and user preference than prior methods. |
| [video][bibtex][project page] |
2024
| SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors |
|---|
| Dave Zhenyu Chen, Haoxuan Li, Hsin-Ying Lee, Sergey Tulyakov, Matthias Nießner |
| CVPR 2024 |
| We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors. At its core, SceneTex proposes a multiresolution texture field to implicitly encode the mesh appearance. To further secure the style consistency across views, we introduce a cross-attention decoder to predict the RGB values by cross-attending to the pre-sampled reference locations in each instance. |
| [video][bibtex][project page] |