Given the widespread adoption of depth-sensing acquisition devices, RGB-D videos and related data/media have gained considerable traction in various aspects of daily life. Consequently, conducting salient object detection (SOD) in RGB-D videos presents a highly promising and evolving avenue. Despite ...
Saliency object detectionRGB-D imageRecurrent convolutional neural networkSingle stream networkSalient object detection for RGB-D images aims to utilize color and depth information to automatically localize objects of human interest in the scene and reduce the complexity of visual analysis. Different from...
YearPub.TitleLinks 2023 arXiv All in One: RGB, RGB-D, and RGB-T Salient Object Detection Xingzhao Jia, Zhongqiu Zhao, Changlei Dongye, Zhao Zhang Paper/Code2024YearPub.TitleLinks 2024 AppSci Advancing in RGB-D Salient Object Detection: A Survey Ai Chen, Xin Li, Tianxiang He, Junlin...
Salient object detection for RGB-D images aims to utilize color and depth information to automatically localize objects of human interest in the scene and reduce the complexity of visual analysis. Different from existing saliency detection model with double-stream network, salient object detection by ...
Salient object detection, which simulates human visual perception in locating the most significant object(s) in a scene, has been widely applied to various
Fully convolutional neural network has shown advantages in the salient object detection by using the RGB or RGB-D images. However, there is an object-part dilemma since most fully convolutional neural network inevitably leads to an incomplete segmentation of the salient object. Although the capsule ...
Code Issues Pull requests Salient Object Detection in the Deep Learning Era: An In-Depth Survey survey sod saliency salient-object-detection visual-attention saliency-prediction saliency-maps Updated Jan 9, 2021 taozh2017 / RGBD-SODsurvey Star 347 Code Issues Pull requests RGB-D Salient Ob...
(2-D) saliency detection methods. In this letter, a multistage salient object detection framework via minimum barrier distance transform and saliency fusion based on multilayer cellular automata (MCA) is proposed. First, we independently generate the 3-D spatial prior, depth bias, and RGB-produced...
本文全面回顾了RGB-D显著性目标检测的研究进展,包括三大方面:基于深度的salient object detection,基于深度和颜色的salient object detection,以及RGB-D共显著性检测。分析了显著性目标检测和RGB-D显著性目标检测的关系。 尽管RGB-D显著性目标检测方法已经有很多,但是仍存在需要解决的问题:深度图的低质量问题可能会隐形RG...
3,解决的问题是 RGB-D salient object detection 4,解决的问题分为三个层面: modal-specific representation learning---作者提出:a hierarchical cross-modal distillation scheme complementary cue selection---作者提出:residual function cross-modal complement fusion.---作者提出: CNN...