用生成代理修复缺失视角下的物体细节,保持场景一致性
SCORP: Scene-Consistent Object Refinement via Proxy Generation and Tuning
- 先生成物体代理,再通过7自由度对齐逐步优化几何与外观
- 在多个基准上提升新视角合成与几何补全效果
- 适合需要高保真物体重建的场景应用
物体视角缺失是场景重建中的常见问题,因相机路径通常聚焦整体结构而非单个物体。这使得在保持场景级表征准确性的前提下实现高保真物体建模极具挑战。本文提出一种名为SCORP(Scene-Consistent Object Refinement via Proxy Generation and Tuning)的新3D增强框架,利用3D生成先验,在缺失视角下恢复细粒度的物体几何与外观。首先通过3D生成模型替换退化的物体以生成代理;随后通过7-DoF姿态对齐,逐级优化代理的几何与纹理,并通过注册约束增强修正空间与外观不一致。该两阶段代理调优确保了未见视角下原始物体的高保真几何与外观,同时保持空间位置、观测几何与外观的一致性。在多个挑战性基准上,SCORP在新视角合成与几何补全任务中均持续优于近期先进基线方法。
原文摘要 · Abstract (English)
Viewpoint missing of objects is common in scene reconstruction, as camera paths typically prioritize capturing the overall scene structure rather than individual objects. This makes it highly challenging to achieve high-fidelity object-level modeling while maintaining accurate scene-level representation. Addressing this issue is critical for advancing downstream tasks requiring high-fidelity object reconstruction. In this paper, we introduce Scene-Consistent Object Refinement via Proxy Generation and Tuning (SCORP), a novel 3D enhancement framework that leverages 3D generative priors to recover fine-grained object geometry and appearance under missing views. Starting with proxy generation by substituting degraded objects using a 3D generation model, SCORP then progressively refines geometry and texture by aligning each proxy to its degraded counterpart in 7-DoF pose, followed by correcting spatial and appearance inconsistencies through registration-constrained enhancement. This two-stage proxy tuning ensures the high-fidelity geometry and appearance of the original object in unseen views while maintaining consistency in spatial positioning, observed geometry, and appearance. Across challenging benchmarks, SCORP achieves consistent gains over recent state-of-the-art baselines on both novel view synthesis and geometry completion tasks. SCORP is available at https://github.com/PolySummit/SCORP.
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