SCORP: Scene-Consistent Object Refinement via Proxy Generation and Tuning

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Authors: Ziwei Chen, Ziling Liu, Zitong Huang, Mingqi Gao, Feng Zheng
Cited by: 0
References: 62

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 counter-part 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.

Fields of Study & Subjects

Image Processing and 3D Reconstruction Computer Graphics and Visualization Techniques Handwritten Text Recognition Techniques

Publication details

Journal / source
2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Publisher
IEEE
Pages
795–805
Publication date
6 March 2026
Language
EN