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Pytorch Image Quality: Metrics for Image Quality Assessment [PDF]
SSRN Electronic Journal, 2022 20 pages with appendix; 4 ...
Kastryulin, Sergey +3 more
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MUSIQ: Multi-scale Image Quality Transformer [PDF]
IEEE International Conference on Computer Vision, 2021 Image quality assessment (IQA) is an important research topic for understanding and improving visual experience. The current state-of-the-art IQA methods are based on convolutional neural networks (CNNs).
Junjie Ke +4 more
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TOPIQ: A Top-Down Approach From Semantics to Distortions for Image Quality Assessment [PDF]
IEEE Transactions on Image Processing, 2023 Image Quality Assessment (IQA) is a fundamental task in computer vision that has witnessed remarkable progress with deep neural networks. Inspired by the characteristics of the human visual system, existing methods typically use a combination of global ...
Chaofeng Chen +7 more
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StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2 [PDF]
Computer Vision and Pattern Recognition, 2021 Videos show continuous events, yet most - if not all - video synthesis frameworks treat them discretely in time. In this work, we think of videos of what they should be - time-continuous signals, and extend the paradigm of neural representations to build
Ivan Skorokhodov +2 more
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No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the perceptual image quality in accordance with subjective evaluations, it is a complex and unsolved problem due to the absence of the pristine reference image.
S. Golestaneh +2 more
semanticscholar +1 more source
MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual quality of images in accordance with human subjective perception. Unfortunately, existing NR-IQA methods are far from meeting the needs of predicting accurate quality scores on ...
Sidi Yang +6 more
semanticscholar +1 more source
Sensors, 2023 The projection of a point cloud onto a 2D camera image is relevant in the case of various image analysis and enhancement tasks, e.g., (i) in multimodal image processing for data fusion, (ii) in robotic applications and in scene analysis, and (iii) for ...
Christina Junger +2 more
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Interactive robot teaching based on finger trajectory using multimodal RGB-D-T-data
Frontiers in Robotics and AI, 2023 The concept of Industry 4.0 brings the change of industry manufacturing patterns that become more efficient and more flexible. In response to this tendency, an efficient robot teaching approach without complex programming has become a popular research ...
Yan Zhang +3 more
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Analyzing and Improving the Image Quality of StyleGAN [PDF]
Computer Vision and Pattern Recognition, 2019 The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its characteristic artifacts, and propose changes in both model architecture and training
Tero Karras +5 more
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The Use of Datasets of Bad Quality Images to Define Fundus Image Quality [PDF]
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022 Screening programs for sight-threatening diseases rely on the grading of a large number of digital retinal images. As automatic image grading technology evolves, there emerges a need to provide a rigorous definition of image quality with reference to the grading task.
Menolotto, Matteo, Giardini, Mario E.
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