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Context-aware network for RGB-D salient object detection
Pattern Recognition, 2021Abstract Convolutional neural networks (CNNs) have shown unprecedented success in object representation and detection. Nevertheless, CNNs lack the capability to model context dependencies among objects, which are crucial for salient object detection.
Fangfang Liang +5 more
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Triple-Complementary Network for RGB-D Salient Object Detection
IEEE Signal Processing Letters, 2020Most of the existing RGB-D saliency detectors have tried different strategies to fuse RGB and depth information to generate better saliency detection results. However, the ability of only using RGB image to detect the salient object is ignored in RGB-D saliency detectors.
Rui Huang 0006, Yan Xing, Yaobin Zou
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RGB-D Salient Object Detection: A Review
2019Salient object detection focuses on extracting attractive objects from the scene, which serves as a foundation of various vision tasks. Benefiting from the progress in acquisition devices, the depth cue is convenient to obtain, and is used in salient object detection in RGB-D images in combination with the color cue. In this chapter, we comprehensively
Tongwei Ren, Ao Zhang
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CoCNN: RGB-D deep fusion for stereoscopic salient object detection
Pattern Recognition, 2020Abstract Many convolutional neural network (CNN)-based approaches for stereoscopic salient object detection involve fusing either low-level or high-level features from the color and disparity channels. The former method generally produces incomplete objects, whereas the latter tends to blur object boundaries.
Fangfang Liang +6 more
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DVSOD: RGB-D Video Salient Object Detection
Advances in Neural Information Processing Systems 36, 2023Jingjing Li +4 more
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RGB-D Salient Object Detection by a CNN With Multiple Layers Fusion
IEEE Signal Processing Letters, 2019Recent saliency detectors use depth to improve the precision of the results. However, most of the existing RGB-D saliency detectors only treat depth as an additional feature, which cannot explore the distinguishing ability of the depth map. In this letter, we propose a deep convolutional neural network for RGB-D saliency detection.
Rui Huang 0006, Yan Xing, Zezheng Wang
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Multi-Modal Transformer for RGB-D Salient Object Detection
2022 IEEE International Conference on Image Processing (ICIP), 2022Peipei Song +3 more
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Dual Priors Network for RGB-D Salient Object Detection
2022 IEEE International Conference on Big Data (Big Data), 2022Yuewang Xu +3 more
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Dynamic Selection Network For Rgb-D Salient Object Detection
2022 IEEE International Conference on Image Processing (ICIP), 2022Jinlin Zhou, Zhiming Luo, Shaozi Li
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Aggregate interactive learning for RGB-D salient object detection
Expert Systems with Applications, 2022Jingyu Wu +4 more
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