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
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.
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.