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) aims to search and identify disguised objects that are
hidden in their surrounding environment, thereby deceiving the human visual system. As an …

In this survey, we give an overview of invariant interest point detectors, how they evolved
over time, how they work, and what their respective strengths and weaknesses are. We …

Camouflaged objects attempt to conceal their texture into the background and discriminating
them from the background is hard even for human beings. The main objective of this paper …

How to identify and segment camouflaged objects from the background is challenging.
Inspired by the multi-head self-attention in Transformers, we present a simple masked …

This paper explores a statistical basis for a process often described in computer vision:
image segmentation by region merging following a particular order in the choice of regions …

We present a bottom-up aggregation approach to image segmentation. Beginning with an
image, we execute a sequence of steps in which pixels are gradually merged to produce …

This exploratory paper quests for a stochastic and context sensitive grammar of images. The
grammar should achieve the following four objectives and thus serves as a unified …

Camouflaged objects are generally difficult to be detected in their natural environment even
for human beings. In this paper, we propose a novel bio-inspired network, named the …

Camouflaged object detection has attracted a lot of attention in computer vision. The main
challenge lies in the high degree of similarity between camouflaged objects and their …