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Blind quality assessment of omnidirectional videos using spatio-temporal convolutional neural networks

  • Published:2021-01 Issue: Volume:226 Page:165887
  • ISSN:0030-4026
  • Container-title:Optik
  • language:en
  • Short-container-title:Optik

Author:

Chai Xiongli,Shao Feng

Funder

National Natural Science Foundation of China-Guangdong Joint Fund

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference50 articles.

1. DRL360: 360-degree video streaming with deep reinforcement learning;Zhang,2019

2. Blind image quality measurement by exploiting high order statistics with deep dictionary encoding network;Jiang;IEEE Trans. Instrum. Meas.,2020

3. Blind binocular visual quality predictor using deep fusion network;Zhou;IEEE Trans. Comput. Imaging,2020

4. Unified no-reference quality assessment of singly and multiply distorted stereoscopic images;Jiang;IEEE Trans. Image Process.,2019

5. Optimizing multistage discriminative dictionaries for blind image quality assessment;Jiang;IEEE Trans. Multimedia,2018

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