Seeing the Unseen: Camouflaged Object Detection Beyond the Visible Spectrum

• URL: http://arxiv.org/abs/2608.30355v1
• Date: Mon, 31 Aug 2026 07:14:14 GMT
• Title: Seeing the Unseen: Camouflaged Object Detection Beyond the Visible Spectrum
• Abstract summary: We introduce a novel approach to detect camouflaged objects from the corresponding multispectral inputs.<n>In particular, we propose an end-to-end framework, textbftextitMSFormer, that takes a multispectral camouflaged image as input and predicts a binary mask for it.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent advances in camouflaged object detection (COD) have led to substantial progress in challenging low-visibility scenarios, with pioneering studies demonstrating notable success in localizing objects in camouflaged scenes. Despite these achievements, existing approaches predominantly rely on conventional three-channel RGB imagery, thereby constraining the available visual information to a limited spectral range. Multispectral images offer a wide range of information about a scene by capturing fine-grained spectral signatures. Hence, by leveraging multispectral images for COD, we introduce a novel approach to detect camouflaged objects from the corresponding multispectral inputs. In particular, we propose an end-to-end framework, \textbf{\textit{MSFormer}}, that takes a multispectral camouflaged image as input and predicts a binary mask for it. Additionally, we also provide empirical justification for integrating multispectral bands for this complex low-vision task. Our extensive experiments demonstrate the effectiveness of our method, which outperforms existing methods.

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