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pro vyhledávání: '"Wiedemann, Oliver"'
We introduce a novel Image Quality Assessment (IQA) dataset comprising 6073 UHD-1 (4K) images, annotated at a fixed width of 3840 pixels. Contrary to existing No-Reference (NR) IQA datasets, ours focuses on highly aesthetic photos of high technical q
Externí odkaz:
http://arxiv.org/abs/2406.17472
The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given reference image and a compression algorithm represents the minimal level o
Externí odkaz:
http://arxiv.org/abs/2306.07678
Scale-invariance is an open problem in many computer vision subfields. For example, object labels should remain constant across scales, yet model predictions diverge in many cases. This problem gets harder for tasks where the ground-truth labels chan
Externí odkaz:
http://arxiv.org/abs/2212.05813
Autor:
Su, Shaolin, Lin, Hanhe, Hosu, Vlad, Wiedemann, Oliver, Sun, Jinqiu, Zhu, Yu, Liu, Hantao, Zhang, Yanning, Saupe, Dietmar
An accurate computational model for image quality assessment (IQA) benefits many vision applications, such as image filtering, image processing, and image generation. Although the study of face images is an important subfield in computer vision resea
Externí odkaz:
http://arxiv.org/abs/2207.04904
Akademický článek
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Publikováno v:
Quality & User Experience; 8/18/2023, Vol. 8 Issue 1, p1-16, 16p
