Zerong Zheng

郑泽荣 | 2nd year PhD student

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About Me

Hi, this is Zerong Zheng (郑泽荣). I am currently 2nd year PhD student in Department of Automation, Tsinghua University, advised by Prof. Yebin Liu. My research focuses on in 3D vision and graphics, especially 3D reconstruction, performance capture and so on.

Contact: zrzheng1995 AT foxmail DOT com


Tsinghua University

B.Eng & Ph.D. Student   |   Beijing, China

I began my PhD education in August 2018, and my advisor is Prof. Yebin Liu. Before that, I received a B.Eng degree from Department of Automation, Tsinghua University in July 2018.


Research Intern   |   San Francisco, USA

I am excited to join Facebook Reality Lab @ Sausalito as a research intern this summer, working with Dr. Tony Tung.

University of Southern California

Undergraduate Visiting Scholar   |   Los Angeles, USA

I spent an exciting summer as a visiting researcher at USC Institute for Creative Technologies, working with Prof. Hao Li and Tao Yu. During my visit, I mainly worked on combining body model into dynamic reconstruction to improve the robustness of performance capture system.


DeepHuman: 3D Human Reconstruction from a Single Image

Z. Zheng, T. Yu, Y. Wei, Q. Dai, Y. Liu

IEEE International Conference on Computer Vision 2019  --   ICCV 2019 Oral

We propose DeepHuman, a deep learning based framework for 3D human reconstruction from a single RGB image. We also contribute THuman, a 3D real-world human model dataset containing approximately 7000 models.

Webpage  ·  Paper ·  Video ·  Bibtex

SimulCap : Single-View Human Performance Capture with Cloth Simulation

T. Yu, Z. Zheng, Y. Zhong, J. Zhao, Q. Dai, G. Pons-Moll, Y. Liu

IEEE Conference on Computer Vision and Pattern Recognition 2019   --   CVPR 2019

This paper proposes a new method for live free-viewpoint human performance capture with dynamic details (e.g., cloth wrinkles) using a single RGBD camera. By incorporating cloth simulation into the performance capture pipeline, we can generate plausible cloth dynamics and cloth-body interactions.

Webpage  ·  Paper  ·  Video ·  Bibtex

HybridFusion: Real-time Performance Capture Using a Single Depth Sensor and Sparse IMUs

Z. Zheng, T. Yu, H. Li, K. Guo, Q. Dai, L. Fang, Y. Liu

European Conference on Computer Vision 2018   --   ECCV 2018

We propose a light-weight and highly robust real-time human performance capture method based on a single depth camera and sparse inertial measurement units (IMUs).

Webpage  ·  Paper ·  Video ·  Bibtex

DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor

T. Yu, Z. Zheng, K. Guo, J. Zhao, Q. Dai, H. Li, G. Pons-Moll, Y. Liu

IEEE Conference on Computer Vision and Pattern Recognition 2018   --   CVPR 2018 Oral

We propose DoubleFusion, a new real-time system to simultaneously reconstruct detailed geometry, non-rigid motion and the inner human body shape from a single depth camera.

Webpage  ·  Paper ·  Video ·  Bibtex



Future Scholar Fellowship, Tsinghua University

Excellent Bachelor Thesis Award, Tsinghua University


Academic Excellence Award, Tsinghua-GuangYao Scholarship, Tsinghua University

Excellence Award & Scholarship for Technological Innovation, Tsinghua University


Academic Excellence Award, Tsinghua-Hengda Scolarship, Tsinghua University

Excellence Award for Technological Innovation, Tsinghua University


Academic Excellence Award & Scholarship, Tsinghua University