用拼图操作分离3D风格与内容，实现快速一致的风格迁移。
Jigsaw3D: Disentangled 3D Style Transfer via Patch Shuffling and Masking
- 通过打乱和掩码参考图像块，剥离语义保留风格统计特征。
- 在多个视图上保持一致性，延迟显著低于现有方法。
- 适合需要快速生成无缝纹理的3D内容创作者使用。
可控3D风格迁移旨在重绘3D资产，使其纹理匹配参考图像，同时保持结构完整性和多视角一致性。现有方法通常依赖直接注入参考风格标记或从2D扩散模型中蒸馏得分，导致每场景优化开销大，且常将风格与语义纠缠。我们提出Jigsaw3D，一种基于多视图扩散的流水线，将风格与内容解耦，实现快速、视图一致的风格化。核心思想是利用拼图操作——对参考图像块进行空间打乱和随机掩码，抑制物体语义并隔离风格统计量（如色彩调色板、笔触、纹理）。这些风格线索通过参考到视图的交叉注意力集成至多视图扩散模型，生成以输入网格为条件的视图一致风格化渲染结果，随后将风格烘焙至表面，生成无缝纹理。在标准3D风格迁移基准上，Jigsaw3D实现了高风格保真度和多视图一致性，延迟显著降低，并能泛化至部分遮挡参考风格、多物体场景风格化及可重复纹理生成。
原文摘要 · Abstract (English)
Controllable 3D style transfer seeks to restyle a 3D asset so that its textures match a reference image while preserving the integrity and multi-view consistency. The prevalent methods either rely on direct reference style token injection or score-distillation from 2D diffusion models, which incurs heavy per-scene optimization and often entangles style with semantic content. We introduce Jigsaw3D, a multi-view diffusion based pipeline that decouples style from content and enables fast, view-consistent stylization. Our key idea is to leverage the jigsaw operation - spatial shuffling and random masking of reference patches - to suppress object semantics and isolate stylistic statistics (color palettes, strokes, textures). We integrate these style cues into a multi-view diffusion model via reference-to-view cross-attention, producing view-consistent stylized renderings conditioned on the input mesh. The renders are then style-baked onto the surface to yield seamless textures. Across standard 3D stylization benchmarks, Jigsaw3D achieves high style fidelity and multi-view consistency with substantially lower latency, and generalizes to masked partial reference stylization, multi-object scene styling, and tileable texture generation. Project page is available at: https://babahui.github.io/jigsaw3D.github.io/
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