[2603.01602] YCDa: YCbCr Decoupled Attention for Real-time Realistic Camouflaged Object Detection

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.01602 (cs) [Submitted on 2 Mar 2026] Title:YCDa: YCbCr Decoupled Attention for Real-time Realistic Camouflaged Object Detection Authors:PeiHuang Zheng, Yunlong Zhao, Zheng Cui, Yang Li View a PDF of the paper titled YCDa: YCbCr Decoupled Attention for Real-time Realistic Camouflaged Object Detection, by PeiHuang Zheng and 3 other authors View PDF HTML (experimental) Abstract:Human vision exhibits remarkable adaptability in perceiving objects under camouflage. When color cues become unreliable, the visual system instinctively shifts its reliance from chrominance (color) to luminance (brightness and texture), enabling more robust perception in visually confusing environments. Drawing inspiration from this biological mechanism, we propose YCDa, an efficient early-stage feature processing strategy that embeds this "chrominance-luminance decoupling and dynamic attention" principle into modern real-time detectors. Specifically, YCDa separates color and luminance information in the input stage and dynamically allocates attention across channels to amplify discriminative cues while suppressing misleading color noise. The strategy is plug-and-play and can be integrated into existing detectors by simply replacing the first downsampling layer. Extensive experiments on multiple baselines demonstrate that YCDa consistently improves performance with negligible overhead as shown in Fig. Notably, YCDa-YOLO12s achieves a...