A Completely Blind Video Integrity Oracle

By Anish Mittal, Michele A. Saad, A. Bovik. IEEE Transactions on Image Processing, 2016

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UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content (2020, methodology): “Among these, NIQE, IL-NIQE, and VIIDEO are “completely blind” (opinion-unaware (OU)), since no training is required to build them.”
Two-Level Approach for No-Reference Consumer Video Quality Assessment (2019, methodology): “Pixel-based models use a raw video signal solely as an input [4]–[5], [7]–[10], [12], and hybrid models combine features from the bitstream with features extracted from the”
FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling (2022, methodology): “Classical VQA Methods Classical VQA methods [31,29,20,36,35,25] handcrafted features to evaluate video quality.”
Large-Scale Study of Perceptual Video Quality (2018, methodology): “NIQE[36] and VIIDEO [39] are training-free models capable of outputting quality scores on video.”
Quality Assessment of In-the-Wild Videos (2019, methodology): “Unfortunately, the evaluation of current state-of-the-art NR-VQA methods [28, 35] on these video databases shows a poor performance [10, 23, 31, 42].”