Chao Xu

I am a Ph.D. candidate 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 are focused on the fields of computer vision, robotics, and cognitive science. I actively engaged in pushing the boundaries of generalizable object understanding and enhancing 3D vision through diffusion models, visual-language models (VLMs), and large language models (LLMs).

Email / CV / Google Scholar / Twitter / Github

Research

	One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization Minghua Liu, Chao Xu, Haian Jin, Linghao Chen, Mukund Varma T, Zexiang Xu, Hao Su NeurIPS 2023 Paper / Project / Code Star More faithful (adherent to input image) than any other Image-to-3D AIGC, including Shap-E (OpenAI, May 2023).
	GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts Haoran Geng, Helin Xu, Chengyang Zhao, Chao Xu, Li Yi, Siyuan Huang, He Wang CVPR 2023* Highlight (10% of accepted, scores: 5, 5, 5) Paper / Project / Code We learn parts on articulated objects across categories.
	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 Paper / Video We discover part affordances on 3D objects across categories under weak supervision.

Modified from Jon Barron's.