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Cited by 412

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Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection

Zhao, Jia-Xing, Cao, Yang, Fan, Deng-Ping, Cheng, Ming-Ming, Li, Xuan-Yi, Zhang, Le·2019·2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Abstract

The large availability of depth sensors provides valuable complementary information for salient object detection (SOD) in RGBD images. However, due to the inherent difference between RGB and depth information, extracting features from the depth channel using ImageNet pre-trained backbone models and fusing them with RGB features directly are sub-optimal. In this paper, we utilize contrast prior, which used to be a dominant cue in none deep learning based SOD approaches, into CNNs-based architecture to enhance the depth information. The enhanced depth cues are further integrated with RGB features for SOD, using a novel fluid pyramid integration, which can make better use of multi-scale cross-modal features. Comprehensive experiments on 5 challenging benchmark datasets demonstrate the superiority of the architecture CPFP over 9 state-of-the-art alternative methods.

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Metadata

Authors
Zhao, J.-X., Cao, Y., Fan, D.-P., Cheng, M.-M., Li, X.-Y., & Zhang, L.
Venue
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Publisher
IEEE
Published
2019-06
Pages
3922-3931
ISSN
1063-6919 (ISSN-L)
OpenAlex
W2948300571
Cited by
412
References
4
FWCI
23.53
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection. https://app.cochat.ai/papers/10.1109/cvpr.2019.00405
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Zhao, J.-X., Cao, Y., Fan, D.-P., Cheng, M.-M., Li, X.-Y., & Zhang, L. (2019). Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2019.00405

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