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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 …
Segment anything is not always perfect: An investigation of sam on different real-world applications
Abstract Recently, Meta AI Research approaches a general, promptable segment anything
model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B) …
model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B) …
Sam-adapter: Adapting segment anything in underperformed scenes
The emergence of large models, also known as foundation models, has brought significant
advancements to AI research. One such model is Segment Anything (SAM), which is …
advancements to AI research. One such model is Segment Anything (SAM), which is …
Zoom in and out: A mixed-scale triplet network for camouflaged object detection
Explicit visual prompting for low-level structure segmentations
We consider the generic problem of detecting low-level structures in images, which includes
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …
SAM Fails to Segment Anything?--SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More
The emergence of large models, also known as foundation models, has brought significant
advancements to AI research. One such model is Segment Anything (SAM), which is …
advancements to AI research. One such model is Segment Anything (SAM), which is …
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 …