activity
20192021
most citedJL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

29 citations · 34 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV20214 cited

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection

Wenbo Zhang, Ge-Peng Ji, Zhuo Wang +2

RGB-D salient object detection (SOD) recently has attracted increasing research interest by benefiting conventional RGB SOD with extra depth information. However, existing RGB-D SO…

cs.CV20211 cited

BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection

Wenbo Zhang, Yao Jiang, Keren Fu +1

Depth information has been proved beneficial in RGB-D salient object detection (SOD). However, depth maps obtained often suffer from low quality and inaccuracy. Most existing RGB-D…

cs.CV2021

RGB-D Salient Object Detection via 3D Convolutional Neural Networks

Qian Chen, Ze Liu, Yi Zhang +3

RGB-D salient object detection (SOD) recently has attracted increasing research interest and many deep learning methods based on encoder-decoder architectures have emerged. However…

cs.CV2020

Siamese Network for RGB-D Salient Object Detection and Beyond

Keren Fu, Deng-Ping Fan, Ge-Peng Ji +3

Existing RGB-D salient object detection (SOD) models usually treat RGB and depth as independent information and design separate networks for feature extraction from each. Such sche…

cs.CV202029 cited

JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

Keren Fu, Deng-Ping Fan, Ge-Peng Ji +1

This paper proposes a novel joint learning and densely-cooperative fusion (JL-DCF) architecture for RGB-D salient object detection. Existing models usually treat RGB and depth as i…

cs.CV2019

Unsupervised Many-to-Many Image-to-Image Translation Across Multiple Domains

Ye Lin, Keren Fu, Shenggui Ling +1

Unsupervised multi-domain image-to-image translation aims to synthesis images among multiple domains without labeled data, which is more general and complicated than one-to-one ima…