To date, the widely-adopted way to perform fixation collection in panopt...
Although weakly-supervised techniques can reduce the labeling effort, it...
Although deep salient object detection (SOD) has achieved remarkable
pro...
Recent research advances in salient object detection (SOD) could largely...
Camouflaged object detection (COD), segmenting objects that are elegantl...
Video saliency detection (VSD) aims at fast locating the most attractive...
The existing state-of-the-art (SOTA) video salient object detection (VSO...
Nonnegative matrix factorization (NMF) has been widely studied in recent...
Thanks to the rapid advances in deep learning techniques and the wide
av...
Automatically detecting/segmenting object(s) that blend in with their
su...
Subspace clustering methods have been widely studied recently. When the
...
The real human attention is an interactive activity between our visual s...
Previous RGB-D salient object detection (SOD) methods have widely adopte...
Fully convolutional networks have shown outstanding performance in the
s...
The screen content images (SCIs) usually comprise various content types ...
The existing fusion based RGB-D salient object detection methods usually...
The current main stream methods formulate their video saliency mainly fr...
Previous video salient object detection (VSOD) approaches have mainly fo...
Compared with the conventional hand-crafted approaches, the deep learnin...
In this paper, we propose a new Semi-Nonnegative Matrix Factorization me...
Existing nonnegative matrix factorization methods focus on learning glob...
Robust principal component analysis (RPCA) has drawn significant attenti...