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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 11–20 of 44 papers

TitleStatusHype
SegGPT Meets Co-Saliency Scene—0
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object DetectionCode1
Co-Salient Object Detection with Co-Representation PurificationCode1
Memory-aided Contrastive Consensus Learning for Co-salient Object DetectionCode4
Co-Salient Object Detection With Uncertainty-Aware Group Exchange-Masking—0
Generalised Co-Salient Object Detection—0
GCoNet+: A Stronger Group Collaborative Co-Salient Object DetectorCode4
Global-and-Local Collaborative Learning for Co-Salient Object DetectionCode0
Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object DetectionCode1
A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object DetectionCode2
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