Yulin Liu

Yulin Liu | 刘雨霖

I’m a 2nd year Ph.D student at Computer Science & Engineering Department, UC San Diego, where I am honored to be advised by Prof. Hao Su. I received my Bachelor degree at Department of Physics, Peking University, where I am fortunate to be advised Prof. He Wang.

Email / CV / Github / Google Scholar

News

[2025/06] 🎉 AdaDexGrasp has been accepted to IROS 2025 as oral presentation!
[2023/09] 😊 I join UC, San Diego for Ph.D. under supervision of Prof. Hao Su!
[2023/03] 🎉 RotationNormFlow has been accepted to CVPR 2023!

Research

I'm building dexterous robots that can learn like we do. 🤖 I'm recently interested in using human demonstrations, captured via teleoperation and hand tracking, to teach robots complex manipulation skills. My long-term goal is to make them an essential part in our daily lives. I'm open to collaborations, feel free to contact me!

Publications are listed by recency. Key papers are in the Selected tab.

	Learning Adaptive Dexterous Grasping from Single Demonstrations Liangzhi Shi, Yulin Liu, Lingqi Zeng, Bo Ai, Zhengdong Hong, Hao Su^†* Website / arXiv / video IROS 2025 International Conference on Intelligent Robots and Systems Oral Presentation TL;DR: AdaDexGrasp learns grasping skills from single demonstrations and uses a vision-language model to adaptively select the correct one based on user instructions.
	ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichseni, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse-kai Chan, Yuan Gao, Xuanlin Li, Tongzhou Mu, Nan Xiao, Arnav Gurha, Viswesh Nagaswamy Rajesh, Yong Woo Choi, Yen-Ru Chen, Zhiao Huang, Roberto Calandra, Rui Chen, Shan Luo, Hao Su^† Website / arXiv / code RSS 2025 Robotics: Science and Systems Oral Presentation @ ICLR-Robot Learning TL;DR: ManiSkill3 is an open-source, GPU-parallelized robotics simulator focusing on generalizable manipulation with contact-rich physics.
	SpaRP: Fast 3D Object Reconstruction and Pose Estimation from Sparse Views Chao Xu, Ang Li, Linghao Chen, Yulin Liu, Ruoxi Shi, Hao Su^†, Minghua Liu^† Website / arXiv ECCV 2024 European Conference on Computer Vision Oral Presentation @ ECCV-CV4Metaverse TL;DR: Given sparse unposed views, we leverage rich priors embedded in multiview diffusion models to predict their poses and reconstruct the 3D shape.
	3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation Hansheng Chen, Bokui Shen, Yulin Liu, Ruoxi Shi, Linqi Zhou, Connor Z. Lin, Jiayuan Gu, Hao Su, Gordon Wetzstein, Leonidas Guibas^† Website / arXiv / code arXiv 2024 TL;DR: 3D-Adapter enables high-quality 3D generation using a 3D feedback module attached to a base image diffusion model for enhanced geometry consistency.
	Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling Yulin Liu, Haoran Liu, Yingda Yin, Yang Wang, Baoquan Chen^†, He Wang^†* Website / arXiv / code / video CVPR 2023 Computer Vision and Pattern Recognition Conference TL;DR: We propose a discrete normalizing flow on SO(3) manifold, through which one can not only effectively express arbitrary distributions on SO(3), but also conditionally build the target distribution given input observations.