VMAF is an on-going project. It has gone through substantial updates since its inception, and even more so after its open sourcing on Github in June 2016. This page attempts to maintain a (non-exhaustive) list of references on VMAF, including tech blogs, academic papers, presentations, etc. VMAF also has a Wikipedia page.
- Toward a practical perceptual video quality metric, June 6, 2016 -- tech blog with VMAF's open sourcing on Github.
- Dynamic Optimizer — a perceptual video encoding optimization framework, March 6, 2018 -- tech blog describing how VMAF is used in an codec-agnostic encoding optimization framework.
- Optimized shot-based encodes: now streaming!, March 9, 2018 -- tech blog describing systems design for the Dynamic Optimizer.
- VMAF: the journey continues, October 25, 2018 -- second techblog on VMAF focus on new features and best practices.
Note that not all ideas in the academic papers below are implemented in the current version of VMAF open-source package (or not yet).
- A. Aaron, Z. Li, M. Manohara, J.Y. Lin, E.C.-H. Wu, and C.-C. J. Kuo, Challenges in cloud based ingest and encoding for high quality streaming media, in Proc. IEEE International Conference on Image Processing, pp. 1732–1736, 2015.
- J. Y. Lin, T. J. Liu, E. C.-H. Wu and C. C. J. Kuo, A fusion-based video quality assessment (FVQA) index, Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific, Siem Reap, 2014.
- J. Y. Lin, R. Song, C.-H. Wu, T. Liu, H. Wang, C.-C. Jay Kuo, MCL-V: A streaming video quality assessment database, Journal of Visual Communication and Image Representation, Volume 30, 2015, Pages 1-9, ISSN 1047-3203,
- J. Y. Lin, C.-H. Wu, I. Katsavounidis, Z. Li, A. Aaron and C.-C. J. Kuo, EVQA: An ensemble-learning-based video quality assessment index, 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Turin, 2015.
- H. Sheikh and A. Bovik, Image information and visual quality. IEEE Transactions on Image Processing. 15 (2): 430–444, 2006.
- S. Li, F. Zhang, L. Ma, K. N. Ngan, Image quality assessment by separately evaluating detail losses and additive impairments. IEEE Transactions on Multimedia. 13 (5): 935–949, 2011.
- Z. Li and C. Bampis, Recover subjective quality scores from noisy measurements, in Proc. Data Compression Conference, April 2017.
- C. G. Bampis, Z. Li, I. Katsavounidis and A. C. Bovik, Recurrent and dynamic models for predicting streaming video quality of experience, in IEEE Transactions on Image Processing, vol. 27, no. 7, pp. 3316-3331, July 2018.
- C. G. Bampis, A. C. Bovik, Learning to predict streaming video QoE: distortions, rebuffering and memory, in arXiv e-print, 2017.
- C. G. Bampis, Z. Li, and A. C. Bovik, SpatioTemporal feature integration and model fusion for full reference video quality assessment, in arXiv e-print, 2018.
- J. Li, L. Krasula, P. Le Callet, Z. Li, Y. Baveye, Quantifying the influence of devices on quality of experience for video streaming, in Proc. Picture Coding Symposium (PCS), San Francisco, 2018.
The papers below independently evaluate the performance of VMAF.
- R. Rassool, VMAF reproducibility: validating a perceptual practical video quality metric, 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Cagliari, 2017, pp. 1-2.
- C. Lee, S. Woo, S. Baek, J. Han, J. Chae and J. Rim, Comparison of objective quality models for adaptive bit-streaming services, 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA), Larnaca, 2017.
- N. Barman, S. Schmidt, S. Zadtootaghaj, M. Martini, S. Möller, An evaluation of video quality assessment metrics for passive gaming video streaming, 23rd Packet Video Workshop 2018 (PV 2018).
- Measuring perceptual video quality at scale by A. Aaron, at Demuxed 2016.
- More efficient encoding for mobile video by A. Aaron, at Video@Scale 2017.
- Measure perceptual video quality with VMAF by Z. Li, at Netflix Industry Wrokshop: Video Encoding at Scale, 2017 IEEE International Conference on Image Processing (ICIP), Beijing, 2017.
- A VMAF model for 4K by Z. Li, T. Vigier and P. Le Callet, at Video Quality Experts Group (VQEG) Meeting in Madrid, March 2018.
- Quantify VMAF model variability using bootstrapping by Z. Li and I. Katsavounidis, at Video Quality Experts Group (VQEG) Meeting in Madrid, March 2018.
- VMAF: the journey continues by Z. Li, at Streaming Media West, Huntington Beach, CA, November 2018.
- Analysis tools in the VMAF open-source package by Z. Li and C. Bampis, at Video Quality Experts Group (VQEG) Meeting in Mountain View, CA, November 2018.