Welcome to the Computer Vision and Learning Group (VLG) at ETH Zürich!

We are a research group within the Insitute of Visual Computing of the Department of Computer Science at ETH Zürich. Our research interest lies in computer vision and the combination with machine learning. We work on discovering and proposing algorithms and implementations for solving high-level visual recognition problems. The goal is to advance the frontier of robust machine perception in real-world settings. Our current research interests include:

Human-scene Interaction. Humans constantly interact with the 3D environment around them. To better understand and model the human-scene interactions, we develop fundamental representations, propose novel algorithms and estabilish new benchmarks. Recent publication

Action and Behavior. We are interesting in understanding the fine-grained details of human action and behavior. We also aim to understand the dynamics, intention and causality of human behaviours from visual input. In particular, we study human action and behavior in the context of real-world 3D enviroments. Recent publication

Human Pose Estimation and Tracking. We study optimization problems for the task of people pose estimation and tracking in real-world crowded scenes. We also study novel learning techniques that connect combinatorial optimization with deep neural networks and blur the boundary between these two model classes. Recent publication


July 2020

2 papers (1 oral + 1 spotlight oral) are accepted at ECCV'20

March 2020

2 papers (1 oral + 1 poster) are accepted at CVPR 2020

January 2020

Siyu will be an area chair for CVPR 2021 and tutorial chair for CVPR 2023

September 2019

Siyu received the ELLIS award for her PhD thesis!

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Recent Publications

Generating 3D People in Scenes without People

Y Zhang, M Hassan, H Neumann, M Black, S Tang
CVPR 2020

Learning to Dress 3D People in Generative Clothing

Q Ma, J Yang, A Ranjan, S Pujades, G Pons-Moll, S Tang, M Black
CVPR 2020

Learning Multi-Human Optical Flow

A Ranjan, D Hoffmann, D Tzionas, S Tang, J Romero, M Black
IJCV 2020

End-to-end Learning for Graph Decomposition

J Song, B Andres, M Black, O Hilliges, S Tang
ICCV 2019

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