Salient object detection techniques in computer vision—A survey
Detection and localization of regions of images that attract immediate human visual attention
is currently an intensive area of research in computer vision. The capability of automatic …
is currently an intensive area of research in computer vision. The capability of automatic …
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 …
Zoom in and out: A mixed-scale triplet network for camouflaged object detection
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 …
LSNet: Lightweight spatial boosting network for detecting salient objects in RGB-thermal images
W Zhou, Y Zhu, J Lei, R Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Most recent methods for RGB (red–green–blue)-thermal salient object detection (SOD)
involve several floating-point operations and have numerous parameters, resulting in slow …
involve several floating-point operations and have numerous parameters, resulting in slow …
Simultaneously localize, segment and rank the camouflaged objects
Camouflage is a key defence mechanism across species that is critical to survival. Common
camouflage include background matching, imitating the color and pattern of the …
camouflage include background matching, imitating the color and pattern of the …
Leveraging auxiliary tasks with affinity learning for weakly supervised semantic segmentation
Semantic segmentation is a challenging task in the absence of densely labelled data. Only
relying on class activation maps (CAM) with image-level labels provides deficient …
relying on class activation maps (CAM) with image-level labels provides deficient …
UC-Net: Uncertainty inspired RGB-D saliency detection via conditional variational autoencoders
In this paper, we propose the first framework (UCNet) to employ uncertainty for RGB-D
saliency detection by learning from the data labeling process. Existing RGB-D saliency …
saliency detection by learning from the data labeling process. Existing RGB-D saliency …
Weakly supervised segmentation of COVID19 infection with scribble annotation on CT images
Segmentation of infections from CT scans is important for accurate diagnosis and follow-up
in tackling the COVID-19. Although the convolutional neural network has great potential to …
in tackling the COVID-19. Although the convolutional neural network has great potential to …