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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 1–10 of 44 papers

TitleStatusHype
Visual Consensus Prompting for Co-Salient Object DetectionCode1
CONDA: Condensed Deep Association Learning for Co-Salient Object Detection—0
CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection—0
Self-supervised co-salient object detection via feature correspondence at multiple scalesCode0
Discriminative Consensus Mining with A Thousand Groups for More Accurate Co-Salient Object DetectionCode0
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics—0
Towards Open-World Co-Salient Object Detection with Generative Uncertainty-aware Group Selective Exchange-MaskingCode0
Co-Salient Object Detection with Semantic-Level Consensus Extraction and Dispersion—0
Zero-Shot Co-salient Object Detection FrameworkCode1
Advancing Referring Expression Segmentation Beyond Single ImageCode1
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