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3D Visual Saliency: An Independent Perceptual Measure or a Derivative of 2D Image Saliency?
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 While 3D visual saliency aims to predict regional importance of 3D surfaces in agreement with human visual perception and has been well researched in computer vision and graphics, latest work with eye-tracking experiments shows that state-of-the-art 3D ...
Ran Song +4 more
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A Plug-and-Play Scheme to Adapt Image Saliency Deep Model for Video Data [PDF]
IEEE transactions on circuits and systems for video technology (Print), 2020 With the rapid development of deep learning techniques, image saliency deep models trained solely by spatial information have occasionally achieved detection performance for video data comparable to that of the models trained by both spatial and temporal
Yunxiao Li +4 more
semanticscholar +1 more source
Convex Optimization Method for Quantifying Image Quality Induced Saliency Variation
IEEE Access, 2021 Visual saliency plays a significant role in image quality assessment. Image distortions cause shift of saliency from its original places. Being able to measure such distortion-included saliency variation (DSV) contributes towards the optimal use of ...
Pengfei Guo +5 more
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Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features [PDF]
مدیریت مهندسی و رایانش نرم, 2020 One of the most important processing steps in the human vision system is the detection of a scene saliency map. Since saliency map can be applied to algorithms such as segmentation, compression and image retrieval, Researchers have focused on providing ...
Mohammad Shouryabi +1 more
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Underwater Image Saliency Detection Via Attention-based Mechanism
Journal of Physics: Conference Series, 2022 Due to complex lighting circumstances and other factors, visual saliency recognition of underwater images is not as good as visual saliency detection models that function well on land when applied to underwater environments.
Lidan Liu, Weiwei Yu
semanticscholar +1 more source
Salient target detection in hyperspectral image based on visual attention
IET Image Processing, 2021 Salient target detection in hyperspectral image is a significant task in image segmentation, target tracking, image classification and so on. Many existing saliency detection algorithms for hyperspectral image detection cannot present the boundary of the
Minghua Zhao +5 more
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Mesh Saliency: An Independent Perceptual Measure or A Derivative of Image Saliency?
Computer Vision and Pattern Recognition, 2021 While mesh saliency aims to predict regional importance of 3D surfaces in agreement with human visual perception and is well researched in computer vision and graphics, latest work with eye-tracking experiments shows that state-of-the-art mesh saliency ...
R. Song +4 more
semanticscholar +1 more source
RGB-T Image Saliency Detection via Collaborative Graph Learning [PDF]
IEEE transactions on multimedia, 2019 Image saliency detection is an active research topic in the community of computer vision and multimedia. Fusing complementary RGB and thermal infrared data has been proven to be effective for image saliency detection.
Zhengzheng Tu +5 more
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Saliency Map Estimation for Omni-Directional Image Considering Prior Distributions [PDF]
arXiv, 2018 In recent years, the deep learning techniques have been applied to the estimation of saliency maps, which represent probability density functions of fixations when people look at the images. Although the methods of saliency-map estimation have been actively studied for 2-dimensional planer images, the methods for omni-directional images to be utilized ...
Tatsuya Suzuki, Takao Yamanaka
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Deep saliency models learn low-, mid-, and high-level features to predict scene attention
Scientific Reports, 2021 Deep saliency models represent the current state-of-the-art for predicting where humans look in real-world scenes. However, for deep saliency models to inform cognitive theories of attention, we need to know how deep saliency models prioritize different ...
Taylor R. Hayes, John M. Henderson
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