RankIQA: Learning from Rankings for No-reference Image Quality Assessment

ICCV 2017 Xialei LiuJoost van de WeijerAndrew D. Bagdanov

We propose a no-reference image quality assessment (NR-IQA) approach that learns from rankings (RankIQA). To address the problem of limited IQA dataset size, we train a Siamese Network to rank images in terms of image quality by using synthetically generated distortions for which relative image quality is known... (read more)

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