GLOSS：用于忠实参考引导纹理填充的几何局部自相似性学习
GLOSS: Geometric Local Self-Similarity Learning for Faithful Reference-Guided Texture Fill
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中文总结 AI 辅助
本研究提出GLOSS模型，利用几何局部自相似性，以数据需求低、可控性强的方式实现忠实参考引导的纹理填充，在3D纹理生成任务中表现优于或媲美基线模型，且作为Blender插件获专业人员认可。
中文摘要 AI 辅助
利用条件图像生成器，纹理艺术家可为现有3D形状探索多种单视图外观。尽管已取得显著进展，但最先进的生成方法仍难以在严格遵循精细尺度几何细节和单视图参考的同时生成完整物体纹理，几乎无艺术家指导空间。此外，当前自动模型缺乏灵活性，无法让艺术家以交互可控方式从不同来源探索多种纹理。与基于大型3D数据集训练、从全局指导生成完整物体纹理的方法不同，本研究探索一种局部且数据需求较低的纹理处理方法，具备明确的艺术家控制能力。我们利用许多自然和人造形状中存在的几何自相似性及几何-纹理相关性，训练特定形状的局部纹理生成与补全模型。该模型从现有图像模型先验和单个3D形状中学习，通过关注一组几何感知参考补丁获得指导。训练后的特定形状网络可通过逐补丁修复将任何新颖参考迁移至完整目标物体纹理。我们展示该模型相比强大的图像条件纹理生成基线具有更优或相当的质量，表明局部纹理处理是一个有前景的研究方向。此外，本模型还支持由艺术家选择参考引导的局部几何条件纹理修复，可泛化至PBR材质和 unseen 网格以进行纹理迁移。我们将新型纹理填充功能作为Blender插件进行试点，多名3D纹理专业人员试用后对模型的可控性、实用性和创作可能性给出积极反馈。
英文摘要
Using conditional image generators, texture artists can explore many single-view looks for an existing 3D shape. Despite impressive progress, state-of-the-art generative methods still struggle to generate a full object texture while closely adhering to fine scale geometric detail and single view references, leaving little room for artists guidance. Furthermore, current automatic models lack the flexibility for artist to explore multiple textures from varied sources in an interactive and controllable manner. Unlike methods trained on large 3D datasets that generate full object textures from global guidance, our work explores a local and less data-hungry approach to texture with explicit artist control. We leverage the geometric self-similarity and geometry-texture correlation existing in many natural and man-made shapes; and train a shape-specific local texture generation and completion model. This model learns from existing image model priors and a single 3D shape, and is guided by attending to a set of geometry-aware reference patches. The trained shape-specific network can transfer any novel reference to the full target object texture through patchwise inpainting. We show improved or comparable quality to strong image-conditioned texture generation baselines, suggesting local texturing as a promising research direction. Our model also enables local geometry-conditioned texture inpainting, guided by artist-selected references, and generalizes to PBR materials and unseen meshes for texture transfer. We piloted our novel texture fill capability as a Blender addon with several 3D texturing professionals who reported positive feedback on the model's controllability, practical usefulness, and creative affordances.
发表机构
- Princeton University（普林斯顿大学）
- NVIDIA（英伟达）
- University of Toronto（多伦多大学）
机构由 AI 辅助整理，请以论文原文为准。
