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Chong Xia | 夏冲
I'm a second-year PhD student in the Department of Electronic Engineering at Tsinghua University , advised by Prof. Yueqi Duan. In 2024, I obtained my B.Eng. in the Department of Automation, Tsinghua University.
My research interest lies in 3D Vision and Embodied AI. If you are interested in working with me, please feel free to drop me an email.
Email  / 
CV  / 
Github
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News
2026-02: One paper on SimReady Scene Reconstruction is accepted by CVPR 2026 Highlight.
2026-02: One paper on Online 3D Reconstruction is accepted by CVPR 2026 Findings.
2025-06: One paper on World Generation is accepted by ICCV 2025.
2024-02: One paper on Embodied Perception is accepted by CVPR 2024.
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Preprints
*Equal contribution †Project leader
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ReplicateAnyScene: Zero-Shot Video-to-3D Composition via Textual-Visual-Spatial Alignment
Mingyu Dong*,
Chong Xia*,
Mingyuan Jia,
Weichen Lyu,
Long Xu ,
Zheng Zhu ,
Yueqi Duan
Arxiv, 2026
[arXiv]
[Code]
[Project Page]
We propose ReplicateAnyScene, a framework for fully automated and zero-shot compositional 3D reconstruction from casually captured videos. Our method extracts and aligns cross-modal priors from vision foundation models to generate semantically coherent and physically plausible 3D scenes.
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Selected Publications
*Equal contribution †Project leader
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SimRecon: SimReady Compositional Scene Reconstruction from Real Videos
Chong Xia*,
Kai Zhu*,
Zizhuo Wang,
Fangfu Liu ,
Zhizheng Zhang ,
Yueqi Duan
Computer Vision and Pattern Recognition (CVPR), 2026, Highlight
[arXiv]
[Code]
[Project Page]
In this paper, we propose a novel compositional scene reconstruction framework, coined SimRecon, that implements a "Perception-Generation-Simulation" pipeline with specialized bridging modules to ensure high visual fidelity and physical plausibility.
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OnlineX: Unified Online 3D Reconstruction and Understanding with Active-to-Stable State Evolution
Chong Xia,
Fangfu Liu ,
Yule Wang,
Yize Pang,
Yueqi Duan
Computer Vision and Pattern Recognition (CVPR), 2026, Findings
[arXiv]
[Code]
[Project Page]
To enable online 3D reconstruction from streaming images, we propose OnlineX, a framework that jointly models visual appearance and language fields through a novel decoupled memory state evolution.
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ScenePainter: Semantically Consistent Perpetual 3D Scene Generation with Concept Relation Alignment
Chong Xia,
Shengjun Zhang ,
Fangfu Liu ,
Chang Liu,
Khodchaphun Hirunyaratsameewong,
Yueqi Duan
International Conference on Computer Vision (ICCV), 2025
[arXiv]
[Code]
[Project Page]
In this paper, we introduce a novel world generation framework, coined ScenePainter, to direct the iterative scene generation process with semantically consistent scene concepts and relations.
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Memory-based Adapters for Online 3D Scene Perception
Xiuwei Xu* ,
Chong Xia*,
Ziwei Wang ,
Linqing Zhao ,
Yueqi Duan ,
Jie Zhou ,
Jiwen Lu
Computer Vision and Pattern Recognition (CVPR), 2024
[arXiv]
[Code]
[Project Page]
We propose a model and task-agnostic plug-and-play module, which converts offline 3D scene perception models (receive reconstructed point clouds) to online perception models (receive streaming RGB-D videos).
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