RGB-D salient object detection: A survey
Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …
significant object (s) in a scene, has been widely applied to various computer vision tasks …
Vision-based robotic gras** from object localization, object pose estimation to grasp estimation for parallel grippers: a review
This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …
conclude three key tasks during vision-based robotic gras**, which are object localization …
Visual saliency transformer
Existing state-of-the-art saliency detection methods heavily rely on CNN-based
architectures. Alternatively, we rethink this task from a convolution-free sequence-to …
architectures. Alternatively, we rethink this task from a convolution-free sequence-to …
SwinNet: Swin transformer drives edge-aware RGB-D and RGB-T salient object detection
Convolutional neural networks (CNNs) are good at extracting contexture features within
certain receptive fields, while transformers can model the global long-range dependency …
certain receptive fields, while transformers can model the global long-range dependency …
CIR-Net: Cross-modality interaction and refinement for RGB-D salient object detection
Focusing on the issue of how to effectively capture and utilize cross-modality information in
RGB-D salient object detection (SOD) task, we present a convolutional neural network …
RGB-D salient object detection (SOD) task, we present a convolutional neural network …
Specificity-preserving RGB-D saliency detection
RGB-D saliency detection has attracted increasing attention, due to its effectiveness and the
fact that depth cues can now be conveniently captured. Existing works often focus on …
fact that depth cues can now be conveniently captured. Existing works often focus on …
Suppress and balance: A simple gated network for salient object detection
Most salient object detection approaches use U-Net or feature pyramid networks (FPN) as
their basic structures. These methods ignore two key problems when the encoder …
their basic structures. These methods ignore two key problems when the encoder …
LSNet: Lightweight spatial boosting network for detecting salient objects in RGB-thermal images
Most recent methods for RGB (red–green–blue)-thermal salient object detection (SOD)
involve several floating-point operations and have numerous parameters, resulting in slow …
involve several floating-point operations and have numerous parameters, resulting in slow …
Calibrated RGB-D salient object detection
Complex backgrounds and similar appearances between objects and their surroundings are
generally recognized as challenging scenarios in Salient Object Detection (SOD). This …
generally recognized as challenging scenarios in Salient Object Detection (SOD). This …
BBS-Net: RGB-D salient object detection with a bifurcated backbone strategy network
Multi-level feature fusion is a fundamental topic in computer vision for detecting, segmenting
and classifying objects at various scales. When multi-level features meet multi-modal cues …
and classifying objects at various scales. When multi-level features meet multi-modal cues …