SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 44 papers

TitleStatusHype
CONDA: Condensed Deep Association Learning for Co-Salient Object Detection—0
Co-saliency Detection for RGBD Images Based on Multi-constraint Feature Matching and Cross Label Propagation—0
Co-Saliency Detection via Looking Deep and Wide—0
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
Co-Salient Object Detection With Uncertainty-Aware Group Exchange-Masking—0
CoSformer: Detecting Co-Salient Object with Transformers—0
Show:102550
← PrevPage 4 of 5Next →

No leaderboard results yet.