Deep-BVQM: A Deep-learning Bitstream-based Video Quality Model-Reference-Cited by-同舟云学术

Deep-BVQM: A Deep-learning Bitstream-based Video Quality Model

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM International Conference on Multimedia
language:
Short-container-title:

Author:

Jamshidi Avanaki Nasim¹,Schmidt Steven²,Michael Thilo¹,Zadtootaghaj Saman³,Möller Sebastian⁴

Affiliation:

1. Quality and Usability Lab, Technische Universität Berlin, Berlin, Germany

2. Sony Interactive Entertainment, Sony, Berlin, Germany

3. Advance Technology Group, Dolby Laboratories, Berlin, Germany

4. Quality and Usability Lab, Technische Universität Berlin & Speech and Language Tech., DFKI, Berlin, Germany

Funder

European Union?s Horizon 2020 research and innovation programme

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3503161.3548374

Reference16 articles.

1. Markus Utke , Saman Zadtootaghaj , Steven Schmidt , Sebastian Bosse , and Sebastian Möller . NDNetGaming-Development of a No-Reference Deep CNN for Gaming Video Quality Prediction . Multimedia Tools and Applications , pages 1 -- 23 , 2020 . Markus Utke, Saman Zadtootaghaj, Steven Schmidt, Sebastian Bosse, and Sebastian Möller. NDNetGaming-Development of a No-Reference Deep CNN for Gaming Video Quality Prediction. Multimedia Tools and Applications, pages 1--23, 2020.

2. Rakesh Rao Ramachandra Rao , Steve Göring , Robert Steger , Saman Zadtootaghaj , Nabajeet Barman , Stephan Fremerey , Sebastian Möller , and Alexander Raake . A large-scale evaluation of the bitstream-based video-quality model itu-t p. 1204.3 on gaming content . In 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP) , pages 1 -- 6 . IEEE, 2020 . Rakesh Rao Ramachandra Rao, Steve Göring, Robert Steger, Saman Zadtootaghaj, Nabajeet Barman, Stephan Fremerey, Sebastian Möller, and Alexander Raake. A large-scale evaluation of the bitstream-based video-quality model itu-t p. 1204.3 on gaming content. In 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), pages 1--6. IEEE, 2020.

3. Joel Jung , Xiang Li , and Shan Liu . New indicator to reflect sudden quality variations of gaming content for P.BBQCG. Itu-t contribution c.588 , ITU-T Study Group 12 , Geneva , 2021 . Joel Jung, Xiang Li, and Shan Liu. New indicator to reflect sudden quality variations of gaming content for P.BBQCG. Itu-t contribution c.588, ITU-T Study Group 12, Geneva, 2021.

4. Netflix. VMAF - Video Multi-Method Assessment Fusion. https://github.com/Netflix/vmaf. [Online: Accessed 09-December-2021]. Netflix. VMAF - Video Multi-Method Assessment Fusion. https://github.com/Netflix/vmaf. [Online: Accessed 09-December-2021].

5. ITU-T Recommendation P.1203. Parametric Bitstream-Based Quality Assessment of Progressive Download and Adaptive Audiovisual Streaming Services Over Reliable Transport . International Telecommunication Union , Geneva , 2017 . ITU-T Recommendation P.1203. Parametric Bitstream-Based Quality Assessment of Progressive Download and Adaptive Audiovisual Streaming Services Over Reliable Transport. International Telecommunication Union, Geneva, 2017.