AI RESEARCH
M2Retinexformer: Multi-Modal Retinexformer for Low-Light Image Enhancement
arXiv CS.CV
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ArXi:2605.12556v1 Announce Type: new Low-light image enhancement is challenging due to complex degradations, including amplified noise, artifacts, and color distortion. While Retinex-based deep learning methods have achieved promising results, they primarily rely on single-modality RGB information. We propose M2Retinexformer (Multi-Modal Retinexformer), a novel framework that extends Retinexformer by incorporating depth cues, luminance priors, and semantic features within a progressive refinement pipeline.