Jingzhi Bao
B.Eng., The Chinese University of Hong Kong, Shenzhen (2025)My research focuses on multi-modal understanding and 3D foundation models. I am currently working on technical scaling of foundation models to production-ready standards.
Education
University of Illinois Urbana-Champaign (UIUC)
Master in Computer Science Sep. 2025 - Present
The Chinese University of Hong Kong, Shenzhen
B.Eng. in Computer Science and Engineering Sep. 2021 - July 2025
Nanyang Technological University (NTU)
Exchange Student Aug. 2023 - Dec. 2023
Experience
Lightspeed Studios, Tencent Games
Research Intern Feb. 2025 - Aug. 2025
MeshyAI
Research Collaboration 2025
University of California, Merced
Visiting Student June 2024 - Dec. 2024
Future Network of Intelligence Institute (FNii)
Research Intern July 2023 - Dec. 2023
Publications
CaliTex: Geometry-Calibrated Attention for View-Coherent 3D Texture Generation
Chenyu Liu, Hongze Chen, Jingzhi Bao, Lingting Zhu, Runze Zhang, Weikai Chen, Zeyu Hu, Yingda Yin, Keyang Luo, Xin Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
A framework of geometry-calibrated attention (geo-aligned attention + condition-routed attention) achieves strong texture alignment with 3D structure. CaliTex produces cross-view consistent textures outperforming both open-source and commercial methods (Hunyuan3D 2.1/3.0).
arXivCaliTex: Geometry-Calibrated Attention for View-Coherent 3D Texture Generation
Chenyu Liu, Hongze Chen, Jingzhi Bao, Lingting Zhu, Runze Zhang, Weikai Chen, Zeyu Hu, Yingda Yin, Keyang Luo, Xin Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
A framework of geometry-calibrated attention (geo-aligned attention + condition-routed attention) achieves strong texture alignment with 3D structure. CaliTex produces cross-view consistent textures outperforming both open-source and commercial methods (Hunyuan3D 2.1/3.0).
LumiTex: Towards High-Fidelity PBR Texture Generation with Illumination Context
Jingzhi Bao*, Hongze Chen*, Lingting Zhu, Chenyu Liu, Runze Zhang, Keyang Luo, Zeyu Hu, Weikai Chen, Yingda Yin, Xin Wang, Zehong Lin, Jun Zhang, Xiaoguang Han
International Conference on Learning Representations (ICLR), 2026
A product-ready level PBR generation method that surpasses SoTA open-source and commercial methods (Hunyuan3D 2.1, Meshy-6, Tripo AI v3).
LumiTex: Towards High-Fidelity PBR Texture Generation with Illumination Context
Jingzhi Bao*, Hongze Chen*, Lingting Zhu, Chenyu Liu, Runze Zhang, Keyang Luo, Zeyu Hu, Weikai Chen, Yingda Yin, Xin Wang, Zehong Lin, Jun Zhang, Xiaoguang Han
International Conference on Learning Representations (ICLR), 2026
A product-ready level PBR generation method that surpasses SoTA open-source and commercial methods (Hunyuan3D 2.1, Meshy-6, Tripo AI v3).
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models
Jingzhi Bao, Xueting Li, Ming-Hsuan Yang
arXiv preprint, 2024
We present Tex4D, a zero-shot framework that fuses 3D geometric priors from mesh sequences with the generative power of video diffusion models to produce multi-view, temporally consistent 4D textures.
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models
Jingzhi Bao, Xueting Li, Ming-Hsuan Yang
arXiv preprint, 2024
We present Tex4D, a zero-shot framework that fuses 3D geometric priors from mesh sequences with the generative power of video diffusion models to produce multi-view, temporally consistent 4D textures.
Photometric Inverse Rendering: Shading Cues Modeling and Reflectance Regularization
Jingzhi Bao, Guanying Chen, Shuguang Cui
International Conference on 3D Vision (3DV), 2025
A differentiable inverse rendering framework that jointly optimizes lighting and materials for photometric images, achieving accurate self-shadow handling and inter-reflection estimation. DINO-based feature distillation delivers more consistent surface reflectance decomposition.
Photometric Inverse Rendering: Shading Cues Modeling and Reflectance Regularization
Jingzhi Bao, Guanying Chen, Shuguang Cui
International Conference on 3D Vision (3DV), 2025
A differentiable inverse rendering framework that jointly optimizes lighting and materials for photometric images, achieving accurate self-shadow handling and inter-reflection estimation. DINO-based feature distillation delivers more consistent surface reflectance decomposition.