Adaptive Guidance Learning for Camouflaged Object Detection

arXiv:2405.02824v1 Announce Type: new
Abstract: Camouflaged object detection (COD) aims to segment objects visually embedded in their surroundings, which is a very challenging task due to the high similarity between the objects and the background. To address it, most methods often incorporate additional information (e.g., boundary, texture, and frequency clues) to guide feature learning for better detecting camouflaged objects from the background. Although progress has been made, these methods are basically individually tailored to specific auxiliary cues, thus lacking adaptability …

arxiv cs.cv detection guidance object type