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I'm a final-year PhD candidate in CS at UIUC, working with Prof. Shenlong Wang and Prof. Saurabh Gupta. I received my master's degree in CS from UCSD, advised by Prof. Xiaolong Wang. Before that, I received my bachelor's degree in EE from Tsinghua University. My research focuses on generative modeling and 3D computer vision, with particular interest in video generation, motion generation, and animation/simulation. My long-term goal is to build physically-grounded world models. Google Scholar / Github / Twitter
I am graduating in Spring 2026 and looking for industry or academic positions. |
Email: shaowei3@illinois.edu |
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Ponimator: Unfolding Interactive Pose for Versatile Human-Human Interaction Animation
Shaowei Liu, Chuan Guo*, Bing Zhou*, Jian Wang* International Conference on Computer Vision(ICCV), 2025. [Paper] [Project] [Code] Interaction human-human motion animation and generation anchored on interactive poses. |
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PhysGen3D: Crafting a Miniature Interactive World from a Single Image
Boyuan Chen, Hanxiao Jiang, Shaowei Liu, Saurabh Gupta, Yunzhu Li, Hao Zhao, Shenlong Wang Conference on Computer Vision and Pattern Recognition(CVPR), 2025. [Paper] [Project] [Code] Synthesizes video of a miniature interactive world from a single image. |
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PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generation
Shaowei Liu, Zhongzheng Ren, Saurabh Gupta*, Shenlong Wang* European Conference on Computer Vision (ECCV), 2024. [Paper] [Project] [Code] Image-to-video generation pipeline integrates physical simulation and video diffusion prior. |
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ContactGen: Generative Contact Modeling for Grasp Generation
Shaowei Liu, Yang Zhou, Jimei Yang, Saurabh Gupta*, Shenlong Wang* International Conference on Computer Vision (ICCV), 2023. [Paper] [Project] [Code] We propose a novel object-centric contact representation for hand-object interaction. |
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Building Rearticulable Models for Arbitrary 3D Objects from 4D Point Clouds
Shaowei Liu, Saurabh Gupta*, Shenlong Wang* Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper] [Project] [Code] We build animatable 3D models from arbitrary articulated object point cloud sequence. |
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CASA: Category-agnostic Skeletal Animal Reconstruction
Yuefan Wu*, Zeyuan Chen*, Shaowei Liu, Zhongzheng Ren, Shenlong Wang Conference on Neural Information Processing Systems (NeurIPS), 2022. [Paper] [Project] [Code] we propose category-agnostic 3D animal reconstruction from a monocular video. |
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DexMV: Imitation Learning for Dexterous Manipulation from Human Videos
Yuzhe Qin*, Yueh-Hua Wu*, Shaowei Liu, Hanwen Jiang, Ruihan Yang, Yang Fu, European Conference on Computer Vision (ECCV), 2022. [Paper] [Project] [Code] we propose a new platform and pipeline for dexterous manipulation from videos. |
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Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videos
Shaowei Liu, Subarna Tripathi, Somdeb Majumdar, Xiaolong Wang Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [Paper] [Project] [Code] We propose to forecast future hand-object interactions given an egocentric video. |
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Hand-Object Contact Consistency Reasoning for Human Grasps Generation
Hanwen Jiang* Shaowei Liu*, Jiashun Wang and Xiaolong Wang International Conference on Computer Vision (ICCV), 2021 (Oral). [Paper] [Project] [Code] We propose to generate natural human grasps given a 3D object in the world. |
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Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time
Shaowei Liu*, Hanwen Jiang*, Jiarui Xu, Sifei Liu and Xiaolong Wang Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [Paper] [Project] [Code] We build a joint learning framework for estimating the 3D hand and object poses. |
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Light and Fast Hand Pose Estimation From Spatial-Decomposed Latent Heatmap
Shaowei Liu, Guijin Wang, Pengwei Xie, Cairong Zhang IEEE Access 2020 [Paper] [Bibtex] We present a light and efficient approach for depth-based hand pose estimation. |
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Intel AI Lab
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Adobe Research
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Snap Research
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Nvidia Spatial Intelligence Lab
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