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Rethinking camouflaged object detection: Models and datasets
H Bi, C Zhang, K Wang, J Tong… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
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 …
locate and distinguish the disguised target in complex backgrounds by imitating the human …
Self-support few-shot semantic segmentation
Existing few-shot segmentation methods have achieved great progress based on the
support-query matching framework. But they still heavily suffer from the limited coverage of …
support-query matching framework. But they still heavily suffer from the limited coverage of …
Concealed object detection
We present the first systematic study on concealed object detection (COD), which aims to
identify objects that are visually embedded in their background. The high intrinsic similarities …
identify objects that are visually embedded in their background. The high intrinsic similarities …
A unified transformer framework for group-based segmentation: Co-segmentation, co-saliency detection and video salient object detection
Humans tend to mine objects by learning from a group of images or several frames of video
since we live in a dynamic world. In the computer vision area, many researchers focus on co …
since we live in a dynamic world. In the computer vision area, many researchers focus on co …
Saliency-CCE: exploiting colour contextual extractor and saliency-based biomedical image segmentation
Biomedical image segmentation is one critical component in computer-aided system
diagnosis. However, various non-automatic segmentation methods are usually designed to …
diagnosis. However, various non-automatic segmentation methods are usually designed to …
Dual-awareness attention for few-shot object detection
While recent progress has significantly boosted few-shot classification (FSC) performance,
few-shot object detection (FSOD) remains challenging for modern learning systems. Existing …
few-shot object detection (FSOD) remains challenging for modern learning systems. Existing …
Global-and-local collaborative learning for co-salient object detection
The goal of co-salient object detection (CoSOD) is to discover salient objects that commonly
appear in a query group containing two or more relevant images. Therefore, how to …
appear in a query group containing two or more relevant images. Therefore, how to …
Structure-measure: A new way to evaluate foreground maps
Foreground map evaluation is crucial for gauging the progress of object segmentation
algorithms, in particular in the field of salient object detection where the purpose is to …
algorithms, in particular in the field of salient object detection where the purpose is to …