Many existing methods for salient object detection are performed by over-segmenting images into non-overlapping regions, which facilitate local/global color ...
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Jan 31, 2018 · This paper proposes a novel method, spectral salient object detection, that aims at maintaining objects holistically during pre-segmentation in ...
In this paper, we tackle the challenging task of unsuper- vised salient object detection (SOD) by leveraging spec- tral clustering on self-supervised ...
Mar 23, 2022 · In this paper, we tackle the challenging task of unsupervised salient object detection (SOD) by leveraging spectral clustering on self-supervised features.
In this work, we proposed a salient object detection model on hyperspectral images by applying manifold ranking (MR) on self-supervised Convolutional Neural ...
In this paper, we propose an efficient hyperspectral image salient object detection method through anomaly detection by combining deep learning autoencoders ...
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Many existing methods for salient object detection are performed by over-segmenting images into non-overlapping regions, which facilitate local/global color ...
Salient object detection (SOD) aims to identify the most visually striking objects or regions within images or videos.
Dec 2, 2023 · Abstract:Hyperspectral salient object detection (HSOD) aims to detect spectrally salient objects in hyperspectral images (HSIs).
In computer vision, salient object detection (SOD) that aims at finding out the salient objects in a given image is help- ful to discover the objects and well ...