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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 )

Benchmarks

Greatest papers with code

EGNet: Edge Guidance Network for Salient Object Detection

ICCV 2019 JXingZhao/EGNet

In the second step, we integrate the local edge information and global location information to obtain the salient edge features.

CAMOUFLAGED OBJECT SEGMENTATION CO-SALIENT OBJECT DETECTION

Gradient-Induced Co-Saliency Detection

ECCV 2020 zzhanghub/gicd

Co-saliency detection (Co-SOD) aims to segment the common salient foreground in a group of relevant images.

CO-SALIENT OBJECT DETECTION

Re-thinking Co-Salient Object Detection

7 Jul 2020DengPingFan/CoEGNet

CoSOD is an emerging and rapidly growing extension of salient object detection (SOD), which aims to detect the co-occurring salient objects in a group of images.

CO-SALIENT OBJECT DETECTION

Taking a Deeper Look at Co-Salient Object Detection

CVPR 2020 DengPingFan/CoEGNet

Co-salient object detection (CoSOD) is a newly emerging and rapidly growing branch of salient object detection (SOD), which aims to detect the co-occurring salient objects in multiple images.

CO-SALIENT OBJECT DETECTION