CoFiNet: Unveiling Camouflaged Objects with Multi-Scale Finesse

Understand

Camouflaged Object Detection (COD) is a critical aspect of computer vision aimed at identifying concealed objects, with applications spanning military, industrial, medical and monitoring domains.

• To address the problem of poor detail segmentation effect, we introduce a novel method for camouflage object detection, named CoFiNet.
• Our approach primarily focuses on multi-scale feature fusion and extraction, with special attention to the model's segmentation effectiveness for detailed features, enhancing its ability to effectively detect camouflaged objects.
• CoFiNet adopts a coarse-to-fine strategy.