Zhuangzhe Wu — accepted AI-conference papers

2025

EMD: Explicit Motion Modeling for High-Quality Street Gaussian Splatting

Xiaobao Wei, Qingpo Wuwu, Zhongyu Zhao, Zhuangzhe Wu, Nan Huang, Ming Lu +2

ICCV 2025poster

Photorealistic reconstruction of street scenes is essential for developing real-world simulators in autonomous driving. While recent methods based on 3D/4D Gaussian Splatting (GS) have demonstrated promising results, they still encounter challenges in complex street scenes due to the unpredictable m…

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2025

URDF-Anything: Constructing Articulated Objects with 3D Multimodal Language Model

Zhe Li, Xiang Bai, Jieyu Zhang, Zhuangzhe Wu, Che Xu, Ying Li +2

NeurIPS 2025spotlight

Constructing accurate digital twins of articulated objects is essential for robotic simulation training and embodied AI world model building, yet historically requires painstaking manual modeling or multi-stage pipelines. In this work, we propose \textbf{URDF-Anything}, an end-to-end automatic recon…

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