SCORP: Scene-Consistent Object Refinement via Proxy Generation and Tuning
Ziwei Chen, Ziling Liu, Zitong Huang, Mingqi Gao, Feng Zheng

TL;DR
SCORP is a novel 3D object refinement framework that uses generative priors and proxy tuning to recover detailed object geometry and appearance in scene reconstructions, especially when views are missing.
Contribution
Introduces SCORP, a two-stage proxy generation and tuning method that enhances 3D object reconstruction fidelity using generative priors and spatial alignment.
Findings
Outperforms recent state-of-the-art methods on view synthesis tasks
Achieves significant improvements in geometry completion accuracy
Maintains scene and object consistency across unseen views
Abstract
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…
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Taxonomy
TopicsImage Processing and 3D Reconstruction · Computer Graphics and Visualization Techniques · Handwritten Text Recognition Techniques
