Yiming Zhao

I recently obtained my Master’s degree in Information Technology and Electrical Engineering from ETH Zürich, where I was advised by Prof. Marc Pollefeys and Prof. Christian Holz. My research focused on Human-Object Interaction and Computer Vision. Prior to that, I completed my Bachelor's degree in Information Technology at the Technical University of Munich (TUM), Germany, where I worked on projects related to Signal Processing and Robotics.

During my Master's studies, I completed an 8-month internship at Carl Zeiss Baden-Württemberg, Germany. My work focused on developing a multi-camera synchronization system within an optical object tracking pipeline for vehicle assembly lines. I also worked part-time as a Software Engineer at TALPA Inspection, a spin-off from ETH Zurich, My responsibilities included automating the measurement pipeline for electrochemical detection of corrosion in reinforced concrete.

I am currently seeking a PhD position. My research interests lie in the areas of Computer Vision, Human-Computer Interaction, and Embodied AI.

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Research

My research interests lie at the Computer Vision and Human-Computer Interaction

EgoPressure: A Dataset for Hand Pressure and Pose Estimation in Egocentric Vision
Yiming Zhao*, Taein Kwon*, Paul Streli*, Marc Pollefeys, Christian Holz
Paper / Project Page
Computer Vision and Pattern Recognition (CVPR), 2025
🏆 Highlight (top 3%)

We introduce EgoPressure, a novel egocentric dataset that captures detailed touch contact and pressure interactions. We propose PressureFormer, a novel baseline model for contact pressure estimation

Human from Blur: Human Pose Tracking from Blurry Images
Yiming Zhao, Denys Rozumnyi, Jie Song, Otmar Hilliges, Marc Pollefeys, Martin R. Oswald
Paper
International Conference on Computer Vision (ICCV), 2023

An optimization-based method to extract human body pose from blurry images

SemSpray: Virtual Reality As-Is Semantic Information Labeling Tool for 3D Spatial Data
Yiming Zhao*,Cyprien Fol*, Yuchang Jiang, Tianyu Wu, Iro Armeni
EC3 2022 Conference
Paper

A labeling tool with exocentric mode

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