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 …

Self-support few-shot semantic segmentation

Q Fan, W Pei, YW Tai, CK Tang - European Conference on Computer …, 2022‏ - Springer
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 …

Concealed object detection

DP Fan, GP Ji, MM Cheng… - IEEE transactions on …, 2021‏ - ieeexplore.ieee.org
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 …

A unified transformer framework for group-based segmentation: Co-segmentation, co-saliency detection and video salient object detection

Y Su, J Deng, R Sun, G Lin, H Su… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
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 …

Saliency-CCE: exploiting colour contextual extractor and saliency-based biomedical image segmentation

X Zhou, T Tong, Z Zhong, H Fan, Z Li - Computers in Biology and Medicine, 2023‏ - Elsevier
Biomedical image segmentation is one critical component in computer-aided system
diagnosis. However, various non-automatic segmentation methods are usually designed to …

Dual-awareness attention for few-shot object detection

TI Chen, YC Liu, HT Su, YC Chang… - IEEE Transactions …, 2021‏ - ieeexplore.ieee.org
While recent progress has significantly boosted few-shot classification (FSC) performance,
few-shot object detection (FSOD) remains challenging for modern learning systems. Existing …

Global-and-local collaborative learning for co-salient object detection

R Cong, N Yang, C Li, H Fu, Y Zhao… - IEEE transactions on …, 2022‏ - ieeexplore.ieee.org
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 …

Structure-measure: A new way to evaluate foreground maps

MM Cheng, DP Fan - International Journal of Computer Vision, 2021‏ - Springer
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 …