Yu Liu (刘宇)
I'm Yu Liu, a first year Ph.D. student in Department of Automation, Tsinghua University, advised by Prof. Song-Chun Zhu.
I obtained my bachelor's degree in engineering from the Department of Automation at Tsinghua University, as the monitor of the Tong Class (an AGI program founded by Prof. Song-Chun Zhu).
I'm currently working at General Vision Lab in BIGAI (Beijing Institute for General Artificial Intelligence) as a research intern
advised by Dr. Baoxiong Jia and Dr. Siyuan Huang.
My research interest lies in computer vision, specifically unsupervised object-centric learning, articulated object reconstruction and 3D/4D reconstruction/generation.
My hobbies are reading, music, natural scenery and meditation.
Email  / 
Google Scholar  / 
Github
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Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting
Yu Liu*,
Baoxiong Jia*,
Ruijie Lu,
JunFeng Ni,
Song-Chun Zhu,
Siyuan Huang
ICLR 2025
[Paper]
 
[Project Page]
 
[Code]
We introduce ArtGS, a novel approach that leverages 3D Gaussians to reconstruct articulated objects from 2 states of RGBD images, which achieves state-of-the-art performance in joint parameter estimation and part mesh reconstruction.
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MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes
Ruijie Lu*,
Yixin Chen*,
Junfeng Ni,
Baoxiong Jia,
Yu Liu,
Diwen Wan,
Gang Zeng,
Siyuan Huang
CVPR 2025
[Paper]
[Code]
[Data]
[Project Page]
We introduce MOVIS, which repurposes pre-trained diffusion models for multi-object level novel view synthesis (NVS) in indoor scenes. The key insight lies in incorporating a structure-aware noise scheduler and an auxiliary mask prediction task under novel views.
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SlotLifter: Slot-guided Feature Lifting for Learning Object-centric Radiance Fields
Yu Liu*,
Baoxiong Jia*,
Yixin Chen,
Siyuan Huang
ECCV 2024
[Paper]
 
[Project Page]
 
[Code]
We propose SlotLifter, a novel object-centric radiance model that aims to address the challenges of scene reconstruction and decomposition via slot-guided feature lifting.
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Improving Object-centric Learning With Query Optimization
Baoxiong Jia*,
Yu Liu*,
Siyuan Huang
ICLR 2023
[Paper]
 
[Project Page]
 
[Code]
We proposed BO-QSA for (1) initializing Slot-Attention modules with learnable queries and
(2) optimizing the model with bi-level optimization.
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Selected Awards and Honors
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- Tsinghua University outstanding undergraduate thesis
- Student of the Year 2023, Department of Automation, Tsinghua University
- Tsinghua University Comprehensive Excellent Award (2020 & 2022)
- Tsinghua Science and Technology Innovation Excellence Award (2021)
- Research Star Award, Beijing Institute for General Artificial Intelligence(BIGAI)
- Huang Yicong Scholarship, Research Excellence Award
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