Zekun Li

Zekun Li

Brown University

Hi! My name is Zekun Li (李泽坤). I am a first-year Ph.D. student in Computer Science at Brown University, working with Prof. Srinath Sridhar at Interactive 3D Vision & Learning Lab.

Before studying at Brown, I received my B. Eng. degree with honors in Computer Science at the University of Electronic Science and Technology of China (UESTC). My undergraduate research advisor is Prof. Zhao Kang. Previously, I have enriched my research experience as an intern at Tencent AI Lab. In this summer, I will join Honda Research Institute as a research intern.

My research interest focuses on Generative Models and Computer Graphics. I am keen on combining knowledge-based principles and learning-based networks to achieve robust, responsible, controllable, and creative models for visual content generation. Recently, I mainly focused on character animation and human-X interaction.

I’m always open to collaboration; If you want to work with me, please freely contact me without any hesitation! (○’◡’○)ﾉ

📝 Publications

Under Review
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Surf-D: High-Quality Surface Generation for Arbitrary Topologies using Diffusion Models

Zhengming Yu, Zhiyang Dou, Xiaoxiao Long, Cheng Lin, Zekun Li, Yuan Liu, Norman Müller, Taku Komura, Marc Habermann, Christian Theobalt, Xin Li, Wenping Wang
[paper] [project]

TL;DR: design a novel UDF-based latent diffusion model for shape generation.

CVPR2024
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MANUS: Markerless Grasp Capture using Articulated 3D Gaussians

Chandradeep Pokhariya, Ishaan Nikhil Shah, Angela Xing, Zekun Li, Kefan Chen, Avinash Sharma, Srinath Sridhar
[paper] [project]

TL;DR: provide a new multi-view grasping dataset with contact annotation and articulated Gaussian hand model for the benchmark.

CVPR2023
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Learning Anchor Transformations for 3D Garment Animation

Fang Zhao, Zekun Li, Shaoli Huang, Junwu Weng, Tianfei Zhou, Guosen Xie, Jue Wang, Ying Shan
[paper] [project]

TL;DR: design adaptive anchors to predict 3D garment animation from a body motion sequence, especially for loose-fitting garments.

ECCV2022
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Eliminating Gradient Conflict in Reference-based Line-art Colorization

Zekun Li, Zhengyang Geng, Zhao Kang, Wenyu Chen, and Yibo Yang
[paper] [code]

TL;DR: design a novel BP scheme to solve the gradient issue in Attention.

💬 Professional Service

  • Conference Reviewer: CVPR 2024, SIGGRAPH 2024
  • Google explore CSR: Ph.D. mentor 2024

📖 Educations

  • 2023.09 - 2028.06 (expected), Ph.D. in Computer Science, Brown University.
  • 2019.09 - 2023.06, B. Eng. Degree in Computer Science, University of Electronic Science and Technology of China (UESTC).

💻 Internships

  • 2022.10 - 2023.6, Research Intern, Tencent AI Lab, working on garment animation and generation, supervied by Prof. Fang Zhao.
  • 2020.09 - 2022.09, Research Intern, Cognitive Computing and Intelligent Decision Lab at UESTC, working on image translation, supervied by Prof. Zhao Kang.