Results 101 to 110 of about 1,634 (141)

Context-aware network for RGB-D salient object detection

Pattern Recognition, 2021
Abstract Convolutional neural networks (CNNs) have shown unprecedented success in object representation and detection. Nevertheless, CNNs lack the capability to model context dependencies among objects, which are crucial for salient object detection.
Fangfang Liang, Lijuan Duan, Wei Ma 0008, Yuanhua Qiao, Jun Miao, Qixiang Ye   +5 more
openaire   +1 more source

Triple-Complementary Network for RGB-D Salient Object Detection

IEEE Signal Processing Letters, 2020
Most of the existing RGB-D saliency detectors have tried different strategies to fuse RGB and depth information to generate better saliency detection results. However, the ability of only using RGB image to detect the salient object is ignored in RGB-D saliency detectors.
Rui Huang 0006, Yan Xing, Yaobin Zou
openaire   +1 more source

RGB-D Salient Object Detection: A Review

2019
Salient object detection focuses on extracting attractive objects from the scene, which serves as a foundation of various vision tasks. Benefiting from the progress in acquisition devices, the depth cue is convenient to obtain, and is used in salient object detection in RGB-D images in combination with the color cue. In this chapter, we comprehensively
Tongwei Ren, Ao Zhang
openaire   +1 more source

CoCNN: RGB-D deep fusion for stereoscopic salient object detection

Pattern Recognition, 2020
Abstract Many convolutional neural network (CNN)-based approaches for stereoscopic salient object detection involve fusing either low-level or high-level features from the color and disparity channels. The former method generally produces incomplete objects, whereas the latter tends to blur object boundaries.
Fangfang Liang, Lijuan Duan, Wei Ma 0008, Yuanhua Qiao, Zhi Cai, Jun Miao, Qixiang Ye   +6 more
openaire   +1 more source

RGB-D Point Cloud Registration Based on Salient Object Detection

IEEE Transactions on Neural Networks and Learning Systems, 2022
We propose a robust algorithm for aligning rigid, noisy, and partially overlapping red green blue-depth (RGB-D) point clouds. To address the problems of data degradation and uneven distribution, we offer three strategies to increase the robustness of the iterative closest point (ICP) algorithm.
Teng Wan, Shaoyi Du, Wenting Cui, Runzhao Yao, Yuyan Ge, Ce Li 0001, Yue Gao 0002, Nanning Zheng 0001   +7 more
openaire   +2 more sources

DVSOD: RGB-D Video Salient Object Detection

Advances in Neural Information Processing Systems 36, 2023
Jingjing Li, Wei Ji 0011, Size Wang, Wenbo Li 0001, Li Cheng 0001   +4 more
openaire   +2 more sources

Dual Priors Network for RGB-D Salient Object Detection

2022 IEEE International Conference on Big Data (Big Data), 2022
Yuewang Xu, Li Zhao 0005, Shaoli Cao, Shijie Feng   +3 more
openaire   +1 more source

Dynamic Selection Network For Rgb-D Salient Object Detection

2022 IEEE International Conference on Image Processing (ICIP), 2022
Jinlin Zhou, Zhiming Luo, Shaozi Li
openaire   +1 more source

Aggregate interactive learning for RGB-D salient object detection

Expert Systems with Applications, 2022
Jingyu Wu, Fuming Sun, Rui Xu, Jie Meng, Fasheng Wang   +4 more
openaire   +1 more source

Multi-Modal Transformer for RGB-D Salient Object Detection

2022 IEEE International Conference on Image Processing (ICIP), 2022
Peipei Song, Jing Zhang 0052, Piotr Koniusz, Nick Barnes   +3 more
openaire   +1 more source