I am currently a second-year Ph.D. student at the Center for Vision, Cognition, Learning, and Autonomy (VCLA), University of California, Los Angeles (UCLA), advised by Prof. Song-Chun Zhu.
I received dual bachelor degrees in Computer Engineering from University of Illinois at Urbana-Champaign and Zhejiang University.
My research interests lie in the fields of computer vision, robotics, and cognitive science, especially covering 3D deep learning, object understanding, and cognitive robotics.
My ongoing work focuses on learning generalizable object affordance, a kind of dark matter in AI cognitive systems, by drawing inspiration from embodied cognition and human reasoning.
- June 2022 - Advanced to candidacy.
- Dec. 2021 - Invited talk at MURI Annual Meeting.
- May 2021 - Research intern at Beijing Institute for General Artificial Intelligence (BIGAI).
- Sept. 2020 - Start Ph.D. research at VCLA@UCLA.
PartAfford: Part‑level Affordance Discovery from Cross‑category 3D Objects
Chao Xu, Yixin Chen, He Wang, Song-Chun Zhu, Yixin Zhu, Siyuan Huang
ECCV 2022 Visual Object-oriented Learning meets Interaction Workshop
We present a new task of part-level affordance discovery (PartAfford): Given only the affordance labels per object, the machine is tasked to (i) decompose 3D shapes into parts and (ii) discover how each part of the object corresponds to a certain affordance category.
University of Illinois at Urbana-Champaign
B.S. Computer Engineering | 2016 - 2020
B.Eng. Electronics and Computer Engineering | 2016 - 2020