Zhi Li (李志)

I am a PhD student at Department of Computer Vision and Machine Learning in Max Planck Institute for Informatics, Saarbrücken, Germany, supervised by Prof. Dr. Bernt Schiele, where I work on domain adaptation for autonomous driving. Prior to that, I worked as a research scientist at Department of Visual Computing and Artificial Intelligence in Max Planck Institute for Informatics, collaborating with Prof. Dr. Christian Theobalt and Prof. Dr. Bernt Schiele on 3D human motion capture in deformable scenes.

I got my master's degree in School of Software Engineering, Xi'an Jiaotong University with a thesis project on semi-supervised 2D and 3D human pose estimation, and my bachelor's degree in School of Foreign Language Studies, Xi'an Jiaotong University with a thesis project on authorship attribution.

My research interests lie in image/video perception for autonomous driving and 3D computer vision.

Email  /  CV  /  Google Scholar  /  Github

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Publications
Test-time Domain Adaptation for Monocular Depth Estimation
Zhi Li, Shaoshuai Shi, Bernt Schiele, Dengxin Dai
ICRA, 2023

A test-time domain adaptation framework for monocular depth estimation that achieves state-of-the-art performance in long-term, ever-changing environments.

HULC: 3D HUman Motion Capture with Pose Manifold SampLing and Dense Contact Guidance
Soshi Shimada, Vladislav Golyanik, Zhi Li, Patrick Pérez, Weipeng Xu, Christian Theobalt
ECCV, 2022

A new approach for 3D human motion capture which is aware of the rigid scene geometry.

MoCapDeform: Monocular 3D Human Motion Capture in Deformable Scenes
Zhi Li, Soshi Shimada, Bernt Schiele, Christian Theobalt, Vladislav Golyanik
3DV, 2022   (Best Student Paper Award)

The first approach for 3D human motion capture making aware of the deformable scene geometry.

Monocular 3D Multi-person Pose Estimation via Predicting Factorized Correction Factors
Yu Guo, Lichen Ma, Zhi Li, Xuan Wang, Fei Wang
CVIU, 2021

An effective approach for estimating absolute-scale human poses in the challenging multi-person setting.

On Boosting Single-Frame 3D Human Pose Estimation via Monocular Videos
Zhi Li, Xuan Wang, Fei Wang, Peilin Jiang
ICCV, 2019

A semi-supervised approach to improve the performance of 3D human pose estimation on monocular videos.


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