← 研踪 PaperTrailCVF · CVPR 2026:cvf:1d362eff753e9bd231229c3ab559efc8 · 记录 #1
X-Part: High Fidelity And Structure Coherent Shape Decomposition And Completion
Yan, XinhaoXu, JiachenLi, YangMa, ChangfengYang, YunhanWang, ChunshiZhao, ZiboLai, ZeqiangZhao, YunfeiChen, ZhuoGuo, Chunchao 来源日期（仅到年份） 2026
来源记录日期 2026
雷达观测 2026-11-05 01:57
摘要
Generating 3D shapes at part level is pivotal for downstream applications such as mesh retopology, UV mapping, and 3D printing. However, existing part-based generation methods often lack sufficient controllability and suffer from poor semantically meaningful decomposition. To this end, we introduce X-Part, a controllable generative model designed to decompose a holistic 3D object into semantically meaningful and structurally coherent parts with high geometric fidelity. X-Part exploits the bounding box as prompts for the part generation and injects point-wise semantic features for meaningful decomposition. Furthermore, we design an editable pipeline for interactive part generation. Extensive experimental results show that X-Part achieves state-of-the-art performance in part-level shape generation. This work establishes a new paradigm for creating production-ready, editable, and structurally sound 3D assets. Codes will be released for public research.
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记录 #1 · 2026 · 最新观测版本
X-Part: High Fidelity And Structure Coherent Shape Decomposition And Completion
Generating 3D shapes at part level is pivotal for downstream applications such as mesh retopology, UV mapping, and 3D printing. However, existing part-based generation methods often lack sufficient controllability and suffer from poor semantically meaningful decomposition. To this end, we introduce X-Part, a controllable generative model designed to decompose a holistic 3D object into semantically meaningful and structurally coherent parts with high geometric fidelity. X-Part exploits the bounding box as prompts for the part generation and injects point-wise semantic features for meaningful decomposition. Furthermore, we design an editable pipeline for interactive part generation. Extensive experimental results show that X-Part achieves state-of-the-art performance in part-level shape generation. This work establishes a new paradigm for creating production-ready, editable, and structurally sound 3D assets. Codes will be released for public research.
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