Salient object detection: A survey
Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …
object detection, has attracted great interest in computer vision. While many models have …
A review of co-saliency detection algorithms: Fundamentals, applications, and challenges
Co-saliency detection is a newly emerging and rapidly growing research area in the
computer vision community. As a novel branch of visual saliency, co-saliency detection …
computer vision community. As a novel branch of visual saliency, co-saliency detection …
Rethinking RGB-D salient object detection: Models, data sets, and large-scale benchmarks
The use of RGB-D information for salient object detection (SOD) has been extensively
explored in recent years. However, relatively few efforts have been put toward modeling …
explored in recent years. However, relatively few efforts have been put toward modeling …
Enhanced-alignment measure for binary foreground map evaluation
The existing binary foreground map (FM) measures to address various types of errors in
either pixel-wise or structural ways. These measures consider pixel-level match or image …
either pixel-wise or structural ways. These measures consider pixel-level match or image …
Reverse attention for salient object detection
S Chen, X Tan, B Wang, X Hu - Proceedings of the …, 2018 - openaccess.thecvf.com
Benefit from the quick development of deep learning techniques, salient object detection has
achieved remarkable progresses recently. However, there still exists following two major …
achieved remarkable progresses recently. However, there still exists following two major …
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 filed of salient object detection where the purpose is to …
algorithms, in particular in the filed of salient object detection where the purpose is to …
Learning to detect salient objects with image-level supervision
Abstract Deep Neural Networks (DNNs) have substantially improved the state-of-the-art in
salient object detection. However, training DNNs requires costly pixel-level annotations. In …
salient object detection. However, training DNNs requires costly pixel-level annotations. In …
Review of visual saliency detection with comprehensive information
The visual saliency detection model simulates the human visual system to perceive the
scene and has been widely used in many vision tasks. With the development of acquisition …
scene and has been widely used in many vision tasks. With the development of acquisition …
Deep contrast learning for salient object detection
Salient object detection has recently witnessed substantial progress due to powerful
features extracted using deep convolutional neural networks (CNNs). However, existing …
features extracted using deep convolutional neural networks (CNNs). However, existing …
Knowledge-guided multi-label few-shot learning for general image recognition
Recognizing multiple labels of an image is a practical yet challenging task, and remarkable
progress has been achieved by searching for semantic regions and exploiting label …
progress has been achieved by searching for semantic regions and exploiting label …