Zerong Zheng

郑泽荣 | 2nd-year PhD Student

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.

Background

Tsinghua University

B.Eng & Ph.D. Student
   September 2014 - Present     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.

Facebook Inc.

Research Intern
  June 2019 - September 2019     San Francisco, USA

I was 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
  June 2017 - August 2017     Los Angeles, USA

I spent an exciting summer as a visiting researcher at USC Institute for Creative Technologies, working with Prof. Hao Li.

Research

Robust 3D Self-portraits in Seconds

Z. Li, T. Yu, C. Pan, Z. Zheng, Y. Liu
IEEE Conference on Computer Vision and Pattern Recognition 2020  --  CVPR 2020 Oral

We propose an efficient method for robust 3d self-portraits using a single RGBD camera. Our method can generate detailed 3D self-portraits in seconds and is able to handle challenging clothing topologies.

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.

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.

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).

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 that combines volumetric dynamic reconstruction with datadriven template fitting to simultaneously reconstruct detailed geometry, non-rigid motion and the inner human body shape from a single depth camera.

Distinction

2018

Future Scholar Fellowship, Tsinghua University

Excellent Bachelor Thesis Award, Tsinghua University

2017

Academic Excellence Award, Tsinghua-GuangYao Scholarship, Tsinghua University

Excellence Award & Scholarship for Technological Innovation, Tsinghua University

2016

Academic Excellence Award, Tsinghua-Hengda Scolarship, Tsinghua University

Excellence Award for Technological Innovation, Tsinghua University

2015

Academic Excellence Award & Scholarship, Tsinghua University

Others

Skills
  • C++ (OpenCV, OpenGL, CUDA, Eigen, PCL, Qt, ...)
  • Python (Tensorflow/PyTorch)
  • Matlab, C#
  • LaTex
Languages
  • Chinese (native)
  • English (TOEFL: 101; GRE: 152+170+4.0)
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