Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive
objects exhibiting camouflage. The current boom in terms of techniques and applications …

Camouflaged object detection (COD) is an emerging visual detection task, which aims to
locate and distinguish the disguised target in complex backgrounds by imitating the human …

The recently proposed camouflaged object detection (COD) attempts to segment objects that
are visually blended into their surroundings, which is extremely complex and difficult in real …

Camouflaged object detection (COD) aims to identify objects that are perfectly embedded in
their environment, which has various downstream applications in fields such as medicine …

Camouflaged object segmentation (COS) aims to identify objects that are" perfectly"
assimilate into their surroundings, which has a wide range of valuable applications. The key …

Spotting objects that are visually adapted to their surroundings is challenging for both
humans and AI. Conventional generic/salient object detection techniques are suboptimal for …

Camouflage is a key defence mechanism across species that is critical to survival. Common
camouflage include background matching, imitating the color and pattern of the …

It is challenging to accurately detect camouflaged objects from their highly similar
surroundings. Existing methods mainly leverage a single-stage detection fashion, while …

Automatically detecting/segmenting object (s) that blend in with their surroundings is difficult
for current models. A major challenge is that the intrinsic similarities between such …

Camouflaged object detection (COD) aims to detect/segment camouflaged objects
embedded in the environment, which has attracted increasing attention over the past …