Cosaliency Detection Based on Intrasaliency Prior Transfer and Deep Intersaliency Mining

By Dingwen Zhang, Junwei Han, Jungong Han, Ling Shao. 2016

158 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Sensory Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Fatih Murat Porikli
2. Ling Shao
3. Jianbing Shen
4. Gong Cheng
5. Wenguan Wang
6. Dong Xu
7. Ruigang Yang
8. Nian Liu

In Computer Vision and Pattern Recognition

1. Ling Shao
2. Jianbing Shen
3. Wenguan Wang
4. Junwei Han
5. Ming-Ming Cheng
6. Deng-Ping Fan
7. Gong Cheng
8. Luc Van Gool

In Sensory Systems

1. Jianbing Shen
2. Wenguan Wang
3. Ling Shao
4. Youfu Li
5. Hao Chen
6. Gong Cheng
7. Nian Liu
8. Junwei Han

Citations in the corpus

• Revealing Event Saliency in Unconstrained Video Collection (2017, unknown): “Co-saliency detection [16]–[19] aims at discovering the common and salient objects from two or more relevant images, while the categories, characteristics and locations of these objects are entirely unknown.”
• Saliency-Aware Video Object Segmentation (2018, background): “Top-down approaches [32], [33], [34], [35] are goal-directed and require an explicit understanding of the context of the image.”
• Advanced Deep-Learning Techniques for Salient and Category-Specific Object Detection: A Survey (2018, background): “As an emerging branch of SOD, cosaliency detection [92]–[94] and event saliency detection [95] approaches could also be possible ways for detecting unseen objects/events, because they can learn from any given group of images/videos that contain the co-occurring but unknown objects/events.”
• Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection (2018, background): “* Corresponding author contexts and the difficulty in exploring saliency-specific prior knowledge, a large body of deep convolutional neural networks (CNNs) [11-17] have been designed for RGB-induced salient object detection and have achieved appealing performance.”
• Video Salient Object Detection via Fully Convolutional Networks (2017, background): “been extend to capturing common saliency among related images/videos [41]–[43], [45], [48], inferring the salient”
• CycleSegNet: Object Co-Segmentation With Cycle Refinement and Region Correspondence (2021, unknown): “Co-saliency detection [12], [15], [51], [62]–[64] is a closely related topic which aims to identify the common and salient objects from a group of images.”