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Co-Salient Object Detection

Co-Salient Object Detection is a computational problem that aims at highlighting the common and salient foreground regions (or objects) in an image group. Please also refer to the online benchmark: http://dpfan.net/cosod3k/

( Image credit: Taking a Deeper Look at Co-Salient Object Detection, CVPR2020 )

Papers

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Showing 21–30 of 44 papers

TitleStatusHype
Co-Saliency Detection via Mask-Guided Fully Convolutional Networks With Multi-Scale Label Smoothing—0
Co-Saliency Detection with Co-Attention Fully Convolutional Network—0
Co-salient Object Detection Based on Deep Saliency Networks and Seed Propagation over an Integrated Graph—0
Co-Salient Object Detection with Semantic-Level Consensus Extraction and Dispersion—0
CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection—0
Review of Visual Saliency Detection with Comprehensive Information—0
SegGPT Meets Co-Saliency Scene—0
An Iterative Co-Saliency Framework for RGBD Images—0
Generalised Co-Salient Object Detection—0
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics—0
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