RGB-D Salient Object Detection
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Benchmarks
Most implemented
RGB-D Salient Object Detection: A Survey
Uncertainty Inspired RGB-D Saliency Detection
CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection
Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection
Visual Saliency Transformer
Siamese Network for RGB-D Salient Object Detection and Beyond
Papers
Weakly-Supervised RGB-D Salient Object Detection via SAM-driven Pseudo Annotation and State Space Interaction-based Diffusion
Weakly-supervised RGB-D Salient Object Detection (SOD) is explored to reduce the heavy burden of pixel-level annotations. But scribble annotations lack the structure and details of objects, resulting in inaccurate salien…
RGB-D Salient Object DetectionSTENet: Superpixel Token Enhancing Network for RGB-D Salient Object Detection
Transformer-based methods for RGB-D Salient Object Detection (SOD) have gained significant interest, owing to the transformer's exceptional capacity to capture long-range pixel dependencies. Nevertheless, current RGB-D S…
RGB-D Salient Object DetectionLEAF-Mamba: Local Emphatic and Adaptive Fusion State Space Model for RGB-D Salient Object Detection
RGB-D salient object detection (SOD) aims to identify the most conspicuous objects in a scene with the incorporation of depth cues. Existing methods mainly rely on CNNs, limited by the local receptive fields, or Vision T…
RGB-D Salient Object DetectionComputational EfficiencyLightweight RGB-D Salient Object Detection from a Speed-Accuracy Tradeoff Perspective
Current RGB-D methods usually leverage large-scale backbones to improve accuracy but sacrifice efficiency. Meanwhile, several existing lightweight methods are difficult to achieve high-precision performance. To balance t…
object-detectionObject DetectionRGB-D Salient Object DetectionSalient Object DetectionDual Mutual Learning Network with Global-local Awareness for RGB-D Salient Object Detection
RGB-D salient object detection (SOD), aiming to highlight prominent regions of a given scene by jointly modeling RGB and depth information, is one of the challenging pixel-level prediction tasks. Recently, the dual-atten…
object-detectionObject DetectionRGB-D Salient Object DetectionSalient Object DetectionMambaSOD: Dual Mamba-Driven Cross-Modal Fusion Network for RGB-D Salient Object Detection
The purpose of RGB-D Salient Object Detection (SOD) is to pinpoint the most visually conspicuous areas within images accurately. While conventional deep models heavily rely on CNN extractors and overlook the long-range c…
Mambaobject-detectionObject DetectionRGB-D Salient Object Detection+1