同时修复破损3D物体的形状与纹理，让残缺模型重获完整细节。
Restore3D: Breathing Life into Broken Objects with Shape and Texture Restoration
- 多视角图像联合重建形状与纹理，引入自感知掩码校正机制。
- 在合成与真实数据上均超越现有方法，生成高分辨率一致图像。
- 适合文化遗产修复、工业设计等需要完整3D建模的场景。
修复不完整或损坏的3D物体对文化遗产保护、遮挡物体重建和艺术设计至关重要。现有方法主要关注几何补全，常忽略纹理恢复，且难以处理复杂多样对象。我们提出Restore3D，一种利用多视图图像同时恢复形状与纹理的新框架。为应对训练数据有限问题，构建自动化数据生成流程，从大规模3D数据集中合成成对的不完整-完整样本。Restore3D的核心是多视图模型，结合精心设计的掩码自感知模块与深度感知掩码校正器。该模块学习的校正掩码引导图像融合与增强阶段，保留观测到的形状与纹理模式，优化生成区域，并缓解基础模型的低分辨率限制，最终生成高分辨率、语义连贯且视图一致的多视图图像。随后采用粗到精重建策略，从优化后的多视图图像中恢复出带纹理的详细3D网格。在合成与真实破损物体基准测试中，Restore3D在多视图重建质量和带纹理网格重建上均优于代表性修补、补全与重建基线方法。
原文摘要 · Abstract (English)
Restoring incomplete or damaged 3D objects is crucial for cultural heritage preservation, occluded object reconstruction, and artistic design. Existing methods primarily focus on geometric completion, often neglecting texture restoration and struggling with relatively complex and diverse objects. We introduce Restore3D, a novel framework that simultaneously restores both the shape and texture of broken objects using multi-view images. To address limited training data, we develop an automated data generation pipeline that synthesizes paired incomplete-complete samples from large-scale 3D datasets. Central to Restore3D is a multi-view model, enhanced by a carefully designed Mask Self-Perceiver module with a Depth-Aware Mask Rectifier. The rectified masks learned by the self-perceiver guide an image integration and enhancement phase, helping retain observed shape and texture patterns while refining the generated regions and mitigating the low-resolution limitations of the base model, yielding high-resolution, semantically coherent, and view-consistent multi-view images. A coarse-to-fine reconstruction strategy is then employed to recover detailed textured 3D meshes from refined multi-view images. Experiments on synthetic and real broken-object benchmarks show that Restore3D improves multi-view restoration quality and textured-mesh reconstruction over representative inpainting, completion, and reconstruction baselines in the evaluated settings. Project Page: restore3dx.github.io
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