Depth Awakens: A Depth-perceptual Attention Fusion Network for RGB-D Camouflaged Object Detection

arXiv:2405.05614v1 Announce Type: new
Abstract: Camouflaged object detection (COD) presents a persistent challenge in accurately identifying objects that seamlessly blend into their surroundings. However, most existing COD models overlook the fact that visual systems operate within a genuine 3D environment. The scene depth inherent in a single 2D image provides rich spatial clues that can assist in the detection of camouflaged objects. Therefore, we propose a novel depth-perception attention fusion network that leverages the depth map as an auxiliary input …

arxiv attention cs.cv cs.ni detection fusion network object rgb-d type