Results 31 to 40 of about 15,063 (248)
Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground [PDF]
, 2018 We provide a comprehensive evaluation of salient object detection (SOD) models. Our analysis identifies a serious design bias of existing SOD datasets which assumes that each image contains at least one clearly outstanding salient object in low clutter.
Deng-Ping Fan +5 more
openaire +3 more sources
Salient object detection in hyperspectral imagery [PDF]
2013 IEEE International Conference on Image Processing, 2013 Object detection in hyperspectral images is an important task for many applications. While most traditional methods are pixel-based, many recent efforts have been put on extracting spatial-spectral features. In this paper, we introduce Itti's visual saliency model into the spectral domain for object detection.
Jie Liang 0003 +3 more
openaire +1 more source
Salient Object Detection with Semantic Priors [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Salient object detection has increasingly become a popular topic in cognitive and computational sciences, including computer vision and artificial intelligence research. In this paper, we propose integrating semantic priors into the salient object detection process. Our algorithm consists of three basic steps.
Tam V. Nguyen 0002, Luoqi Liu
openaire +2 more sources
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 +1 more source
Salient Object Detection With Pyramid Attention and Salient Edges
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 This paper presents a new method for detecting salient objects in images using convolutional neural networks (CNNs). The proposed network, named PAGE-Net, offers two key contributions. The first is the exploitation of an essential pyramid attention structure for salient object detection.
Wenguan Wang +4 more
openaire +3 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 +1 more source
A Fusion Underwater Salient Object Detection Based on Multi-Scale Saliency and Spatial Optimization
Journal of Marine Science and Engineering, 2023 Underwater images contain abundant information, but many challenges remain for underwater object detection tasks. Various salient object detection methods may encounter low detection precision, and the segmented map has an incomplete region of the target
Weiliang Huang, Daqi Zhu, Mingzhi Chen
doaj +1 more source
Salient Object Detection via Fusion of Multi-Visual Perception
Applied SciencesSalient object detection aims to distinguish the most visually conspicuous regions, playing an important role in computer vision tasks. However, complex natural scenarios can challenge salient object detection, hindering accurate extraction of objects ...
Wenjun Zhou +6 more
doaj +1 more source
Pluralistic Salient Object Detection
IEEE Transactions on Image ProcessingWe introduce pluralistic salient object detection (PSOD), a novel task aimed at generating multiple plausible salient segmentation results for a given input image. Unlike conventional SOD methods that produce a single segmentation mask for salient objects, this new setting recognizes the inherent complexity of real-world images, comprising multiple ...
Xuelu Feng +6 more
openaire +3 more sources
Optimisation for image salient object detection based on semantic‐aware clustering and CRF
IET Computer Vision, 2020 State‐of‐the‐art optimisation methods for salient object detection neglect that saliency maps of different images usually show different imperfections. Therefore, the saliency maps of some images cannot achieve effective optimisation.
Junhao Chen +3 more
doaj +1 more source