UnReflectAnything: RGB-Only Highlight Removal by Rendering Synthetic Specular Supervision

• URL: http://arxiv.org/abs/2512.09583v2
• Date: Thu, 11 Dec 2025 15:21:30 GMT
• Title: UnReflectAnything: RGB-Only Highlight Removal by Rendering Synthetic Specular Supervision
• Authors: Alberto Rota, Mert Kiray, Mert Asim Karaoglu, Patrick Ruhkamp, Elena De Momi, Nassir Navab, Benjamin Busam,
• Abstract summary: We present UnReflectAnything, an RGB-only framework that removes highlights from a single image.<n>It predicts a highlight map together with a reflection-free diffuse reconstruction.<n>It generalizes across natural and surgical domains where non-Lambertian surfaces and non-uniform lighting create severe highlights.
• Score: 51.72020507506023
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Specular highlights distort appearance, obscure texture, and hinder geometric reasoning in both natural and surgical imagery. We present UnReflectAnything, an RGB-only framework that removes highlights from a single image by predicting a highlight map together with a reflection-free diffuse reconstruction. The model uses a frozen vision transformer encoder to extract multi-scale features, a lightweight head to localize specular regions, and a token-level inpainting module that restores corrupted feature patches before producing the final diffuse image. To overcome the lack of paired supervision, we introduce a Virtual Highlight Synthesis pipeline that renders physically plausible specularities using monocular geometry, Fresnel-aware shading, and randomized lighting which enables training on arbitrary RGB images with correct geometric structure. UnReflectAnything generalizes across natural and surgical domains where non-Lambertian surfaces and non-uniform lighting create severe highlights and it achieves competitive performance with state-of-the-art results on several benchmarks. Project Page: https://alberto-rota.github.io/UnReflectAnything/

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