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Spectral salient object detection [PDF]
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014 © 2014 IEEE. Many existing methods for salient object detection are performed by over-segmenting images into non-overlapping regions, which facilitate local/global color statistics for saliency computation.
Fu, K, Gong, C, Gu, IYH, He, X, Yang, J
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Salient object detection: A survey [PDF]
Computational Visual Media, 2019 Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have been proposed and several applications have emerged, a deep understanding
Ali Borji +4 more
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On the Distribution of Salient Objects in Web Images and Its Influence on Salient Object Detection. [PDF]
PLoS ONE, 2015 In recent years it has become apparent that a Gaussian center bias can serve as an important prior for visual saliency detection, which has been demonstrated for predicting human eye fixations and salient object detection. Tseng et al.
Boris Schauerte, Rainer Stiefelhagen
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Hybrid Attention Asynchronous Cascade Network for Salient Object Detection [PDF]
Mathematics, 2023 The highlighted area or object is defined as the salient region or salient object. For salient object detection, the main challenges are still the clarity of the boundary information of the salient object and the positioning accuracy of the salient ...
Haiyan Yang +3 more
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Hierarchical Salient Object Detection for Assisted Grasping [PDF]
2017 IEEE International Conference on Robotics and Automation (ICRA), 2017 Visual scene decomposition into semantic entities is one of the major challenges when creating a reliable object grasping system. Recently, we introduced a bottom-up hierarchical clustering approach which is able to segment objects and parts in a scene ...
Cremers, Armin Bernd +4 more
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Deep Contrast Learning for Salient Object Detection [PDF]
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 Salient object detection has recently witnessed substantial progress due to powerful features extracted using deep convolutional neural networks (CNNs). However, existing CNN-based methods operate at the patch level instead of the pixel level.
Li, Guanbin, Yu, Yizhou
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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 ...
A Borji +15 more
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Salient Object Detection via Structured Matrix Decomposition [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First,
Hu, W. +5 more
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Depth-Quality-Aware Salient Object Detection [PDF]
IEEE Transactions on Image Processing, 2021 The existing fusion based RGB-D salient object detection methods usually adopt the bi-stream structure to strike the fusion trade-off between RGB and depth (D). The D quality usually varies from scene to scene, while the SOTA bi-stream approaches are depth quality unaware, which easily result in substantial difficulties in achieving complementary ...
Chenglizhao Chen +3 more
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Re-thinking Co-Salient Object Detection [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 In this paper, we conduct a comprehensive study on the co-salient object detection (CoSOD) problem for images. CoSOD is an emerging and rapidly growing extension of salient object detection (SOD), which aims to detect the co-occurring salient objects in a group of images.
Fan, Deng-Ping +7 more
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