No-Reference Quality Assessment of In-Capture Distorted Videos

No-Reference Quality Assessment of In-Capture Distorted Videos

We introduce a no-reference method for the assessment of the quality of videos affected by in-capture distortions due to camera hardware and processing software. The proposed method encodes both quality attributes and semantic content of each video frame by using two Convolutional Neural Networks (C...

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Bibliographic Details
Main Authors:	Mirko Agarla, Luigi Celona, Raimondo Schettini
Format:	Article
Language:	English
Published:	MDPI AG 2020-07-01
Series:	Journal of Imaging
Subjects:	video quality assessment in-capture distortions convolutional neural network recurrent neural network
Online Access:	https://www.mdpi.com/2313-433X/6/8/74

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