Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild

28 May 2020 Weixia Zhang Kede Ma Guangtao Zhai Xiaokang Yang

Performance of blind image quality assessment (BIQA) models has been significantly boosted by end-to-end optimization of feature engineering and quality regression. Nevertheless, due to the distributional shift between images simulated in the laboratory and captured in the wild, models trained on databases with synthetic distortions remain particularly weak at handling realistic distortions (and vice versa)... (read more)

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