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Shaofei Wang

PhD student
CAB G89
shaofei.wang@inf.ethz.ch

Basic Information

I am a PhD student at ETH Zurich , co-advised by Prof. Siyu Tang and Prof. Andreas Geiger. My research topic is computer vision, specifically in building controllable neural implicit representations for human bodies with clothes. I am also interested in differentiable combinatorial optimization and its application in computer vision. Before I came to ETH, I worked as a researcher in Kording Lab at University of Pennsylvania. Even before that, I worked as a senior system engineer at the autonomous driving group of Baidu. I got my Master's degree from University of California, Irvine under supervision of Prof. Charless Fowlkes

Social

Publications


AuthorsShaofei WangKatja SchwarzAndreas GeigerSiyu Tang

Given sparse multi-view videos, ARAH learns animatable clothed human avatars that have detailed pose-dependent geometry/appearance and generalize to out-of-distribution poses.

 

AuthorsShaofei Wang, Marko Mihajlovic, Qianli Ma, Andreas Geiger, Siyu Tang

MetaAvatar is meta-learned model that represents generalizable and controllable neural signed distance fields (SDFs) for clothed humans. It can be fast fine-tuned to represent unseen subjects given as few as 8 monocular depth images.

 

Authors: Shaofei Wang, Andreas Geiger and Siyu Tang

Registering point clouds of dressed humans to parametric human models is a challenging task in computer vision. We propose novel piecewise transformation fields (PTF), a set of functions that learn 3D translation vectors which facilitates occupancy learning, joint-​rotation estimation and mesh registration.