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).
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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
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)
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
Visual Object-oriented Learning meets Interaction Workshop
We discover part affordances on 3D objects across categories under weak supervision.