Jingzhi Bao

CUHK B.Eng., The Chinese University of Hong Kong, Shenzhen (2025)

I am a final-year undergrad. student major in Computer Science at The Chinese University of Hong Kong, Shenzhen. Currently, I am a visiting student at University of California, Merced, working with Dr. Xueting Li, under the supervision of Prof. Ming-Hsuan Yang.

My research focuses on generative models, animation, inverse graphics, and 3D reconstruction.

In addition, I'm an independent developer for MiniProgram, with small steps and rapid development cycles.

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Education
  • The Chinese University of Hong Kong, Shenzhen

    The Chinese University of Hong Kong, Shenzhen

    B.Eng. in Computer Science and Engineering Sep. 2021 - Jul. 2025 (Expected)

  • Nanyang Technological University (NTU)

    Nanyang Technological University (NTU)

    Exchange Student Aug. 2023 - Dec. 2023

Experience
  • University of California, Merced

    University of California, Merced

    Visiting Student June 2024 - Present

  • Future Network of Intelligence Institute (FNii)

    Future Network of Intelligence Institute (FNii)

    Research Intern July 2023 - April 2024

Publications
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models

Jingzhi Bao, Xueting Li, Ming-Hsuan Yang

Under review. 2024

We present Tex4D, a zero-shot approach that integrates inherent 3D geometry knowledge from mesh sequences with the expressiveness of video diffusion models to produce multi-view and temporally consistent 4D textures. Given an untextured mesh sequence and a text prompt as inputs, our method generates multi-view, temporally consistent 4D textures.

[arXiv] [Project Page] [Code]

Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models

Jingzhi Bao, Xueting Li, Ming-Hsuan Yang

Under review. 2024

We present Tex4D, a zero-shot approach that integrates inherent 3D geometry knowledge from mesh sequences with the expressiveness of video diffusion models to produce multi-view and temporally consistent 4D textures. Given an untextured mesh sequence and a text prompt as inputs, our method generates multi-view, temporally consistent 4D textures.

[arXiv] [Project Page] [Code]

Photometric Inverse Rendering: Shading Cues Modeling and Surface Reflectance Regularization

Jingzhi Bao, Guanying Chen, Shuguang Cui

Under review. 2024

This paper addresses the problem of inverse rendering from photometric images. Our method jointly optimizes the light source position to account for the self-shadows in images, and computes indirect illumination using a differentiable rendering layer and an importance sampling strategy. To enhance surface reflectance decomposition, we introduce a new regularization by distilling DINO features to foster accurate and consistent material decomposition.

[arXiv] [Project Page] [Code]

Photometric Inverse Rendering: Shading Cues Modeling and Surface Reflectance Regularization
Photometric Inverse Rendering: Shading Cues Modeling and Surface Reflectance Regularization

Jingzhi Bao, Guanying Chen, Shuguang Cui

Under review. 2024

This paper addresses the problem of inverse rendering from photometric images. Our method jointly optimizes the light source position to account for the self-shadows in images, and computes indirect illumination using a differentiable rendering layer and an importance sampling strategy. To enhance surface reflectance decomposition, we introduce a new regularization by distilling DINO features to foster accurate and consistent material decomposition.

[arXiv] [Project Page] [Code]