Advances in deep concealed scene understanding
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 …
objects exhibiting camouflage. The current boom in terms of techniques and applications …
A systematic review of image-level camouflaged object detection with deep learning
Y Liang, G Qin, M Sun, X Wang, J Yan, Z Zhang - Neurocomputing, 2024 - Elsevier
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 …
hidden in their surrounding environment, thereby deceiving the human visual system. As an …
Camouflaged object detection with feature decomposition and edge reconstruction
Camouflaged object detection (COD) aims to address the tough issue of identifying
camouflaged objects visually blended into the surrounding backgrounds. COD is a …
camouflaged objects visually blended into the surrounding backgrounds. COD is a …
Zoom in and out: A mixed-scale triplet network for camouflaged object detection
Detecting camouflaged object in frequency domain
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 …
their environment, which has various downstream applications in fields such as medicine …
Feature shrinkage pyramid for camouflaged object detection with transformers
Vision transformers have recently shown strong global context modeling capabilities in
camouflaged object detection. However, they suffer from two major limitations: less effective …
camouflaged object detection. However, they suffer from two major limitations: less effective …
Can sam segment anything? when sam meets camouflaged object detection
SAM is a segmentation model recently released by Meta AI Research and has been gaining
attention quickly due to its impressive performance in generic object segmentation …
attention quickly due to its impressive performance in generic object segmentation …
Boundary-guided camouflaged object detection
Camouflaged object detection (COD), segmenting objects that are elegantly blended into
their surroundings, is a valuable yet challenging task. Existing deep-learning methods often …
their surroundings, is a valuable yet challenging task. Existing deep-learning methods often …
Fast camouflaged object detection via edge-based reversible re-calibration network
Abstract Camouflaged Object Detection (COD) aims to detect objects with similar patterns
(eg, texture, intensity, colour, etc) to their surroundings, and recently has attracted growing …
(eg, texture, intensity, colour, etc) to their surroundings, and recently has attracted growing …