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RGB-D Salient Object Detection

RGB-D Salient object detection (SOD) aims at distinguishing the most visually distinctive objects or regions in a scene from the given RGB and Depth data. It has a wide range of applications, including video/image segmentation, object recognition, visual tracking, foreground maps evaluation, image retrieval, content-aware image editing, information discovery, photosynthesis, and weakly supervised semantic segmentation. Here, depth information plays an important complementary role in finding salient objects. Online benchmark: http://dpfan.net/d3netbenchmark.

( Image credit: Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks, TNNLS20 )

Papers

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Showing 26–50 of 88 papers

TitleStatusHype
Depth Quality Aware Salient Object DetectionCode1
Cascade Graph Neural Networks for RGB-D Salient Object DetectionCode1
RGB-D Salient Object Detection: A SurveyCode1
BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy NetworkCode1
Accurate RGB-D Salient Object Detection via Collaborative LearningCode1
A Single Stream Network for Robust and Real-time RGB-D Salient Object DetectionCode1
RGB-D Salient Object Detection with Cross-Modality Modulation and SelectionCode1
Hierarchical Dynamic Filtering Network for RGB-D Salient Object DetectionCode1
Cross-Modal Weighting Network for RGB-D Salient Object DetectionCode1
Bifurcated backbone strategy for RGB-D salient object detectionCode1
Select, Supplement and Focus for RGB-D Saliency DetectionCode1
A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object DetectionCode1
Learning Selective Self-Mutual Attention for RGB-D Saliency DetectionCode1
Is Depth Really Necessary for Salient Object Detection?Code1
Bilateral Attention Network for RGB-D Salient Object DetectionCode1
JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object DetectionCode1
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational AutoencodersCode1
Density Map Guided Object Detection in Aerial ImagesCode1
DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object DetectionCode1
Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale BenchmarksCode1
Dual Mutual Learning Network with Global-local Awareness for RGB-D Salient Object DetectionCode0
A Saliency Enhanced Feature Fusion based multiscale RGB-D Salient Object Detection Network—0
Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion—0
Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object DetectionCode0
HODINet: High-Order Discrepant Interaction Network for RGB-D Salient Object Detection—0
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