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CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion
Han, Junwei1; Chen, Hao1; Liu, Nian1; Yan, Chenggang2; Li, Xuelong3
Contribution Rank3

Salient object detection from RGB-D images aims to utilize both the depth view and RGB view to automatically localize objects of human interest in the scene. Although a few earlier efforts have been devoted to the study of this paper in recent years, two major challenges still remain: 1) how to leverage the depth view effectively to model the depth-induced saliency and 2) how to implement an optimal combination of the RGB view and depth view, which can make full use of complementary information among them. To address these two challenges, this paper proposes a novel framework based on convolutional neural networks (CNNs), which transfers the structure of the RGB-based deep neural network to be applicable for depth view and fuses the deep representations of both views automatically to obtain the final saliency map. In the proposed framework, the first challenge is modeled as a cross-view transfer problem and addressed by using the task-relevant initialization and adding deep supervision in hidden layer. The second challenge is addressed by a multiview CNN fusion model through a combination layer connecting the representation layers of RGB view and depth view. Comprehensive experiments on four benchmark datasets demonstrate the significant and consistent improvements of the proposed approach over other state-of-the-art methods.

KeywordConvolutional Neural Networks (Cnns) Crossview Transfer Multiview Fusion Rgb-d Salient Object Detection
Indexed BySCI ; EI
WOS IDWOS:000447825400013
EI Accession Number20174704417332
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Document Type期刊论文
Corresponding AuthorHan, Junwei
Affiliation1.Northwestern Polytech Univ, Sch Automat, Xian 710129, Shaanxi, Peoples R China
2.Hangzhou Dianzi Univ, Inst Informat & Control, Hangzhou 310018, Zhejiang, Peoples R China
3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning, Xian 710119, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Han, Junwei,Chen, Hao,Liu, Nian,et al. CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion[J]. IEEE TRANSACTIONS ON CYBERNETICS,2018,48(11):3171-3183.
APA Han, Junwei,Chen, Hao,Liu, Nian,Yan, Chenggang,&Li, Xuelong.(2018).CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion.IEEE TRANSACTIONS ON CYBERNETICS,48(11),3171-3183.
MLA Han, Junwei,et al."CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion".IEEE TRANSACTIONS ON CYBERNETICS 48.11(2018):3171-3183.
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