Karrin Hanshew, Terror and Democracy in West Germany (Achim Saupe)

Saupe, Achim

doi:10.5771/9783845251585-318

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2019

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“…The authors of [51], the code of which is not made available, reported high results, but we have been unable to reproduce their numbers, even with more efficient networks. The authors of [52] use a pre-trained ResNet-101 and report high performance on [17,18], but later disclosed [53] that they are unable to reproduce their own results in [52].…”

Section: Introductionmentioning

confidence: 99%

From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality

Ying

Niu

Gupta

et al. 2019

Preprint

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Blind or no-reference (NR) perceptual picture quality prediction is a difficult, unsolved problem of great consequence to the social and streaming media industries that impacts billions of viewers daily. Unfortunately, popular NR prediction models perform poorly on real-world distorted pictures. To advance progress on this problem, we introduce the largest (by far) subjective picture quality database, containing about 40000 real-world distorted pictures and 120000 patches, on which we collected about 4M human judgments of picture quality. Using these picture and patch quality labels, we built deep region-based architectures that learn to produce state-of-the-art global picture quality predictions as well as useful local picture quality maps. Our innovations include picture quality prediction architectures that produce global-to-local inferences as well as local-toglobal inferences (via feedback).

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