Results 51 to 60 of about 622,575 (227)

CoGANet: Co-Guided Attention Network for Salient Object Detection

IEEE Photonics Journal, 2022
Recent salient object detection methods are mainly based on Convolutional Neural Networks (CNNs). Most of them adopt a U-shape architecture to extract and fuse multi-scale features.
Yufei Zhao, Yong Song, Guoqi Li, Yi Huang, Yashuo Bai, Ya Zhou, Qun Hao   +6 more
doaj   +1 more source

TCGNet: Type-Correlation Guidance for Salient Object Detection

IEEE transactions on intelligent transportation systems (Print)
Contrast and part-whole relations induced by deep neural networks like Convolutional Neural Networks (CNNs) and Capsule Networks (CapsNets) have been known as two types of semantic cues for deep salient object detection.
Yi Liu, Ling Zhou, Gengshen Wu, Shoukun Xu, Jungong Han   +4 more
semanticscholar   +1 more source

Adaptive Fusion for RGB-D Salient Object Detection

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   +1 more source

Feature Calibrating and Fusing Network for RGB-D Salient Object Detection

IEEE transactions on circuits and systems for video technology (Print)
Due to their imaging mechanisms and techniques, some depth images inevitably have low visual qualities or have some inconsistent foregrounds with their corresponding RGB images.
Q. Zhang, Qi Qin, Yang Yang, Qiang Jiao, Jungong Han   +4 more
semanticscholar   +1 more source

Salient object detection: a mini review

Frontiers in Signal Processing
This paper presents a mini-review of recent works in Salient Object Detection (SOD). First, We introduce SOD and its application in image processing tasks and applications.
Xiuwenxin Wang, Siyue Yu, Eng Gee Lim, M. L. Dennis Wong, M. L. Dennis Wong   +4 more
doaj   +1 more source

Scribble-based Boundary-aware Network for Weakly Supervised Salient Object Detection in Remote Sensing Images [PDF]

arXiv, 2022
Existing CNNs-based salient object detection (SOD) heavily depends on the large-scale pixel-level annotations, which is labor-intensive, time-consuming, and expensive. By contrast, the sparse annotations become appealing to the salient object detection community.
arxiv  

F3Net: Fusion, Feedback and Focus for Salient Object Detection [PDF]

AAAI Conference on Artificial Intelligence, 2019
Most of existing salient object detection models have achieved great progress by aggregating multi-level features extracted from convolutional neural networks.
Junhang Wei, Shuhui Wang, Qingming Huang
semanticscholar   +1 more source

Selective feature fusion network for salient object detection

IET Computer Vision, 2023
Fully convolutional neural networks have achieved great success in salient object detection, in which the effective use of multi‐layer features plays a critical role. Based on this advantage, many saliency detectors have emerged in recent years, and most
Fengming Sun, Xia Yuan, Chunxia Zhao
doaj   +1 more source

Salient Object Detection: A Discriminative Regional Feature Integration Approach [PDF]

International Journal of Computer Vision, 2013
Feature integration provides a computational framework for saliency detection, and a lot of hand-crafted integration rules have been developed. In this paper, we present a principled extension, supervised feature integration, which learns a random forest
Huaizu Jiang, Zejian Yuan, Ming-Ming Cheng, Yihong Gong, Nanning Zheng, Jingdong Wang   +5 more
semanticscholar   +1 more source

Salient object detection in egocentric videos

IET Image Processing
In the realm of video salient object detection (VSOD), the majority of research has traditionally been centered on third‐person perspective videos. However, this focus overlooks the unique requirements of certain first‐person tasks, such as autonomous ...
Hao Zhang, Haoran Liang, Xing Zhao, Jian Liu, Ronghua Liang   +4 more
doaj   +1 more source