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Learning Salient Feature for Salient Object Detection Without Labels

IEEE Transactions on Cybernetics, 2023
Supervised salient object detection (SOD) methods achieve state-of-the-art performance by relying on human-annotated saliency maps, while unsupervised methods attempt to achieve SOD by not using any annotations. In unsupervised SOD, how to obtain saliency in a completely unsupervised manner is a huge challenge.
Shuo Li   +4 more
openaire   +2 more sources

Salient stills

ACM Transactions on Multimedia Computing, Communications, and Applications, 1992
Salient Stills are a class of images that reflect the aggregation of the temporal changes that occur in a moving-image sequence with the salient features of individual frames preserved. They convey the intended expression of an entire series of moving frames---a visual summary of camera and object movements.
Laura Teodosio, Walter Bender
openaire   +3 more sources

PoolNet+: Exploring the Potential of Pooling for Salient Object Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
We explore the potential of pooling techniques on the task of salient object detection by expanding its role in convolutional neural networks. In general, two pooling-based modules are proposed.
Jiangjiang Liu   +3 more
semanticscholar   +1 more source

Calibrated RGB-D Salient Object Detection

Computer Vision and Pattern Recognition, 2021
Complex backgrounds and similar appearances between objects and their surroundings are generally recognized as challenging scenarios in Salient Object Detection (SOD).
Wei Ji   +10 more
semanticscholar   +1 more source

Salient Features of Histidinemia

Archives of Pediatrics & Adolescent Medicine, 1967
SINCE OUR description in 1961, with Dr. A. Hunter, of two children with an inborn error of histidine metabolism, 18 other cases have been reported (Table). Two thirds of the patients are girls. The youngest patient is 1 month of age and the oldest is 13 years.
H. Ghadimi, M. W. Partington
openaire   +3 more sources

Improved salient objects detection based on salient points

2016 35th Chinese Control Conference (CCC), 2016
In this paper, we propose an effective framework for detecting salient regions of an image via salient points and color contrast. First, the boosting Harris is used to detect highlight points as the salient points, and the convex hull is constructed to separate the foreground regions and the background regions.
Gong Cheng, Lei Guo, Yanbang Zhang
openaire   +2 more sources

Comparing salient point detectors

Pattern Recognition Letters, 2001
The use of salient points in content-based retrieval allows an image index to represent local properties of the image. Classic corner detectors can also be used for this purpose but they have drawbacks when are applied to various natural images mainly because visual features do not need to be corners and corners may gather in small regions.
Sebe, Niculae, M. S. LEW
openaire   +5 more sources

Shifting More Attention to Video Salient Object Detection

Computer Vision and Pattern Recognition, 2019
The last decade has witnessed a growing interest in video salient object detection (VSOD). However, the research community long-term lacked a well-established VSOD dataset representative of real dynamic scenes with high-quality annotations.
Deng-Ping Fan   +3 more
semanticscholar   +1 more source

Hierarchical Alternate Interaction Network for RGB-D Salient Object Detection

IEEE Transactions on Image Processing, 2021
Existing RGB-D Salient Object Detection (SOD) methods take advantage of depth cues to improve the detection accuracy, while pay insufficient attention to the quality of depth information.
Gongyang Li   +5 more
semanticscholar   +1 more source

Attentive Feedback Network for Boundary-Aware Salient Object Detection

Computer Vision and Pattern Recognition, 2019
Recent deep learning based salient object detection methods achieve gratifying performance built upon Fully Convolutional Neural Networks (FCNs). However, most of them have suffered from the boundary challenge. The state-of-the-art methods employ feature
Mengyang Feng, Huchuan Lu, Errui Ding
semanticscholar   +1 more source

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