Rethinking feature aggregation for deep RGB-D salient object detection
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DOI: 10.1016/j.neucom.2020.10.079
Abstract: Abstract Two-stream UNet based architectures are widely used in deep RGB-D salient object detection (SOD) models. However, UNet only adopts a top-down decoder network to progressively aggregate high-level features with low-level ones. In this paper,… read more here.
Keywords: rgb salient; aggregation; level; feature aggregation ... See more keywords
LIANet: Layer Interactive Attention Network for RGB-D Salient Object Detection
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DOI: 10.1109/access.2022.3156935
Abstract: RGB-D salient object detection (SOD) usually describes two modes’ classification or regression problem, namely RGB and depth. The existing RGB-D SOD methods use depth hints to increase the detection performance, meanwhile they focus on the… read more here.
Keywords: network; rgb salient; salient object; interactive attention ... See more keywords
Bi-Directional Progressive Guidance Network for RGB-D Salient Object Detection
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DOI: 10.1109/tcsvt.2022.3144852
Abstract: Most existing RGB-D salient detection models pay more attention to the quality of the depth images, while in some special cases, the quality of RGB images may even have greater impacts on saliency detection, which… read more here.
Keywords: progressive guidance; directional progressive; rgb salient; rgb ... See more keywords
MoADNet: Mobile Asymmetric Dual-Stream Networks for Real-Time and Lightweight RGB-D Salient Object Detection
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DOI: 10.1109/tcsvt.2022.3180274
Abstract: RGB-D Salient Object Detection (RGB-D SOD) aims at detecting remarkable objects by complementary information from RGB images and depth cues. Although many outstanding prior arts have been proposed for RGB-D SOD, most of them focus… read more here.
Keywords: rgb salient; salient object; rgb; dual stream ... See more keywords
Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection
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DOI: 10.1109/tip.2020.3037470
Abstract: Existing RGB-D salient object detection methods treat depth information as an independent component to complement RGB and widely follow the bistream parallel network architecture. To selectively fuse the CNN features extracted from both RGB and… read more here.
Keywords: fusion; object detection; salient object; rgb salient ... See more keywords
Bifurcated Backbone Strategy for RGB-D Salient Object Detection
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DOI: 10.1109/tip.2021.3116793
Abstract: Multi-level feature fusion is a fundamental topic in computer vision. It has been exploited to detect, segment and classify objects at various scales. When multi-level features meet multi-modal cues, the optimal feature aggregation and multi-modal… read more here.
Keywords: strategy; backbone; multi level; rgb salient ... See more keywords
Weakly Supervised RGB-D Salient Object Detection With Prediction Consistency Training and Active Scribble Boosting
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3151999
Abstract: RGB-D salient object detection (SOD) has attracted increasingly more attention as it shows more robust results in complex scenes compared with RGB SOD. However, state-of-the-art RGB-D SOD approaches heavily rely on a large amount of… read more here.
Keywords: object detection; salient object; prediction consistency; weakly supervised ... See more keywords
Learning Implicit Class Knowledge for RGB-D Co-Salient Object Detection With Transformers
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DOI: 10.1109/tip.2022.3185550
Abstract: RGB-D co-salient object detection aims to segment co-occurring salient objects when given a group of relevant images and depth maps. Previous methods often adopt separate pipeline and use hand-crafted features, being hard to capture the… read more here.
Keywords: object detection; class; rgb salient; salient object ... See more keywords
Employing Bilinear Fusion and Saliency Prior Information for RGB-D Salient Object Detection
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DOI: 10.1109/tmm.2021.3069297
Abstract: Multi-modal feature fusion and saliency reasoning are two core sub-tasks of RGB-D salient object detection. However, most existing models employ linear fusion strategies (e.g., concatenation) for multi-modal feature fusion and use a simple coarse-to-fine structure… read more here.
Keywords: saliency; information; fusion; rgb salient ... See more keywords
3-D Convolutional Neural Networks for RGB-D Salient Object Detection and Beyond.
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DOI: 10.1109/tnnls.2022.3202241
Abstract: RGB-depth (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, most existing RGB-D SOD models conduct explicit and controllable cross-modal feature… read more here.
Keywords: neural networks; fusion; rgb salient; decoder ... See more keywords
Siamese Network for RGB-D Salient Object Detection and Beyond
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3073689
Abstract: 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 schemes can easily be constrained by a limited amount of… read more here.
Keywords: salient object; object detection; rgb salient; rgb ... See more keywords