Results 11 to 20 of about 18,850,036 (270)

RGB-D Salient Object Detection Method Based on Multi-Modal Fusion and Contour Guidance

IEEE Access, 2023
Salient object detection is a critical task in the field of computer vision. However, existing detection methods still face certain challenges, such as the inability to effectively integrate multimodal features and the blurring of detection result ...
Yanbin Peng, Mingkun Feng, Zhijun Zheng
doaj   +2 more sources

Adaptive Fusion for RGB-D Salient Object Detection [PDF]

IEEE Access, 2019
RGB-D (red, green, blue, and depth) salient object detection aims to identify the most visually distinctive objects in a pair of color and depth images.
Ningning Wang, Xiaojin Gong
doaj   +5 more sources

Hybrid-Attention Network for RGB-D Salient Object Detection

Applied Sciences, 2020
Depth information has been widely used to improve RGB-D salient object detection by extracting attention maps to determine the position information of objects in an image.
Yuzhen Chen, Wujie Zhou
doaj   +2 more sources

Bifurcated Backbone Strategy for RGB-D Salient Object Detection [PDF]

IEEE Transactions on Image Processing, 2021
A preliminary version of this work has been accepted in ECCV ...
Yingjie Zhai, Deng-Ping Fan, Jufeng Yang, Ali Borji, Ling Shao 0001, Junwei Han 0001, Liang Wang 0001   +6 more
openaire   +5 more sources

Depth‐aware lightweight network for RGB‐D salient object detection

IET Image Processing, 2023
RGB‐D salient object detection (SOD) is to detect salient objects from one RGB image and its depth data. Although related networks have achieved appreciable performance, they are not ideal for mobile devices since they are cumbersome and time‐consuming ...
Liuyi Ling, Yiwen Wang, Chengjun Wang, Shanyong Xu, Yourui Huang   +4 more
doaj   +2 more sources

Middle-level Fusion for Lightweight RGB-D Salient Object Detection [PDF]

CoRR, 2021
Most existing lightweight RGB-D salient object detection (SOD) models are based on two-stream structure or single-stream structure. The former one first uses two sub-networks to extract unimodal features from RGB and depth images, respectively, and then fuses them for SOD.
Nianchang Huang, Qiang Zhang 0020, Jungong Han   +2 more
core   +4 more sources

RGB-D salient object detection based on BC2 FNet network

Xibei Gongye Daxue Xuebao
In the face of complex scene images, the introduction of depth information can greatly improve the performance of salient object detection. However, up-sampling and down-sampling operations in neural networks maybe blur the boundaries of objects in the ...
WANG Feng, CHENG Yongmei
doaj   +3 more sources

Salient Object Detection in RGB-D Videos [PDF]

IEEE Transactions on Image Processing
IEEE TIP (under major revision)
Ao Mou, Yukang Lu, Jiahao He, Dingyao Min, Keren Fu, Qijun Zhao   +5 more
openaire   +4 more sources

Coordinate Attention Filtering Depth-Feature Guide Cross-Modal Fusion RGB-Depth Salient Object Detection

Advances in Multimedia, 2023
Existing RGB + depth (RGB-D) salient object detection methods mainly focus on better integrating the cross-modal features of RGB images and depth maps.
Lingbing Meng, Mengya Yuan, Xuehan Shi, Qingqing Liu, Le Zhange, Jinhua Wu, Ping Dai, Fei Cheng   +7 more
doaj   +2 more sources

Dynamic Message Propagation Network for RGB-D Salient Object Detection

CoRR, 2022
This paper presents a novel deep neural network framework for RGB-D salient object detection by controlling the message passing between the RGB images and depth maps on the feature level and exploring the long-range semantic contexts and geometric information on both RGB and depth features to infer salient objects.
Baian Chen, Zhilei Chen, Xiaowei Hu 0001, Jun Xu 0019, Haoran Xie 0001, Mingqiang Wei, Jing Qin 0001   +6 more
openaire   +4 more sources