Results 181 to 190 of about 333,426 (199)

Modality-Induced Transfer-Fusion Network for RGB-D and RGB-T Salient Object Detection

IEEE transactions on circuits and systems for video technology (Print), 2023
The ability of capturing the complementary information of multi-modality data is critical to the development of multi-modality salient object detection (SOD). Most of existing studies attempt to integrate multi-modality information through various fusion
Gang Chen, Feng Shao, Xiongli Chai, Hangwei Chen, Qiuping Jiang, Xiangchao Meng, Yo-Sung Ho   +6 more
semanticscholar   +1 more source

C$^{2}$DFNet: Criss-Cross Dynamic Filter Network for RGB-D Salient Object Detection

IEEE transactions on multimedia, 2023
The ability to deal with intra and inter-modality features has been critical to the development of RGB-D salient object detection. While many works have advanced in leaps and bounds in this field, most existing methods have not taken their way down into ...
Miao Zhang, Shunyu Yao, Beiqi Hu, Yongri Piao, Wei Ji   +4 more
semanticscholar   +1 more source

BASNet: Boundary-Aware Salient Object Detection

Computer Vision and Pattern Recognition, 2019
Deep Convolutional Neural Networks have been adopted for salient object detection and achieved the state-of-the-art performance. Most of the previous works however focus on region accuracy but not on the boundary quality.
Xuebin Qin, Zichen Zhang, Chenyang Huang, Chao Gao, Masood Dehghan, Martin Jägersand   +5 more
semanticscholar   +1 more source

Cross-Modality Double Bidirectional Interaction and Fusion Network for RGB-T Salient Object Detection

IEEE transactions on circuits and systems for video technology (Print), 2023
RGB-T salient object detection (SOD) aims to detect and segment saliency regions on RGB images and the corresponding thermal maps. The ability of alleviating the modality difference between RGB and thermal modality plays a vital role in the development ...
Zhengxuan Xie, Feng Shao, Gang Chen, Hangwei Chen, Qiuping Jiang, Xiangchao Meng, Yo-Sung Ho   +6 more
semanticscholar   +1 more source

TCNet: Co-Salient Object Detection via Parallel Interaction of Transformers and CNNs

IEEE transactions on circuits and systems for video technology (Print), 2023
The purpose of co-salient object detection (CoSOD) is to detect the salient objects that co-occur in a group of relevant images. CoSOD has been significantly prospered by recent advances in convolutional neural networks (CNNs).
Yanliang Ge, Qiao Zhang, Tian-Zhu Xiang, Cong Zhang, Hongbo Bi   +4 more
semanticscholar   +1 more source

Noise-Sensitive Adversarial Learning for Weakly Supervised Salient Object Detection

IEEE transactions on multimedia, 2023
Weakly supervised salient object detection (WSOD) aims at training saliency detection models with weak supervision. Normally, the WSOD methods use pseudo labels converted from image-level classification labels to train the saliency network.
Yongri Piao, Wei Wu, Miao Zhang, Yongyao Jiang, Huchuan Lu   +4 more
semanticscholar   +1 more source

CATNet: A Cascaded and Aggregated Transformer Network for RGB-D Salient Object Detection

IEEE transactions on multimedia
Salient object detection (SOD) is an important preprocessing operation for various computer vision tasks. Most of existing RGB-D SOD models employ additive or connected strategies to directly aggregate and decode multi-scale features to predict salient ...
Fuming Sun, Pengfei Ren, Bo Yin, Fasheng Wang, Haojie Li   +4 more
semanticscholar   +1 more source

LFRNet: Localizing, Focus, and Refinement Network for Salient Object Detection of Surface Defects

IEEE Transactions on Instrumentation and Measurement, 2023
Salient object detection of surface defects is one of the surface defect detection tasks, which aims at highlighting the defect regions from the surface of strip steel, magnetic tale, road, and so on. However, the performance of existing methods degrades
Bin Wan, Xiaofei Zhou, Bolun Zheng, Haibing Yin, Zunjie Zhu, Hongkui Wang, Yaoqi Sun, Jiyong Zhang, C. Yan   +8 more
semanticscholar   +1 more source

A2SPPNet: Attentive Atrous Spatial Pyramid Pooling Network for Salient Object Detection

IEEE transactions on multimedia, 2023
Recent progress in salient object detection (SOD) mainly depends on the Atrous Spatial Pyramid Pooling (ASPP) module for multi-scale learning. Intuitively, different input images, different pixels, and different network layers may have different ...
Yu Qiu, Yun Liu, Yanan Chen, Jianwen Zhang, Jinchao Zhu, Jing Xu   +5 more
semanticscholar   +1 more source

Towards a Complete and Detail-Preserved Salient Object Detection

IEEE transactions on multimedia
Salient Object Detection (SOD) is dominated by Encoder-Decoder networks which involve multi-scale feature fusion and multi-resolution dense supervision. It is prevalent yet problematic to interpolate feature maps or pool ground truth (GT) to fit the size
Yi Ke Yun, Weisi Lin
semanticscholar   +1 more source