MSU Video Codecs Comparison 2022
Part 1: Hardware encoders
Seventeen Annual Video-Codecs Comparison by MSU
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compression.ru |
Lomonosov Moscow State University (MSU) Graphics and Media Lab |
Dubna International
State University |
Institute for Information Transmission Problems, Russian Academy of Science |
News
- 15.04.2023 Several typos corrected, leaderboard updated (note: several places changed)
- 14.04.2023 Report release
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Description
In MSU Hardware Video Codecs Comparison 2022, we analyzed 14 hardware codecs. There were 3 different speed usecases: 60 fps, 120 fps, 240 fps. 53 FullHD video sequences were used for testing.
Note:
The set of videos used in this comparison consists of less videos than FullHD part because of compatibility issues
Results
- The places below are given by quality scores
- Encoders with scores closer than ~1% share one place
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Best encoder YUV-SSIM, YUV-PSNR |
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Best encoder Y-VMAF (v0.6.3) |
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Best encoder YUV-VMAF (v0.6.3) |
Best GPU encoder |
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Best FPGA encoder |
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Best ASIC encoder |
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The winners vary for different objective quality metrics. The participants were rated using BSQ-rate (enhanced BD-rate) scores [1]. [1] A. Zvezdakova, D. Kulikov, S. Zvezdakov, D. Vatolin, "BSQ-rate: a new approach for video-codec performance comparison and drawbacks of current solutions," 2020. Speed/quality trade-off "Very-fast 60 fps" all sequences, YUV (6:1:1)-SSIM metricSpeed/quality trade-off "Very-fast 60 fps (neglecting lookahead i/o time" on three longest sequences, YUV (6:1:1)-SSIM metricPlease note that this year average video length was selected to be bigger to neglect lookahead effect. That is why two charts are very similar Download
Participants
Comparison RulesHardware-accelerated and ultra-fast codecs testing objectivesThe main goal of this report is the presentation of a comparative evaluation of the quality of new and existing codecs using objective measures of assessment. The comparison was done using settings provided by the developers of each codec. Nevertheless, we required all presets to satisfy minimum speed requirement on the particular use case. The main task of the comparison is to analyze different encoders for the task of transcoding video – e.g., compressing video for personal use. Test Hardware Characteristics for GPU/ASIC encoders
Test Hardware Characteristics for FPGA encoders
See more on Call For Codecs 2022 page VideosVideos for testing set were chosen from MSU video collection via a voting among comparison participants, organizers and an independend expert.
Final video set consists of 53 sequences including new videos from Vimeo and media.xiph.org derf's collection. Descriptions of all test videos are presented in a separate PDF provided with the report. Codec Analysis and Tuning for Codec Developers and Codec UsersComputer Graphics and Multimedia Laboratory of Moscow State University:
Strong and Weak Points of Your Codec
Independent Codec Estimation Comparing to Other Codecs for Different Use-cases
Encoder Features Implementation Optimality AnalysisWe perform encoder features effectiveness (speed/quality trade-off) analysis that could lead up to 30% increase in the speed/quality characteristics of your codec. We can help you to tune your codec and find best encoding parameters.ThanksSpecial thanks to the following contributors of our previous comparisons Contact InformationSubscribe to report updatesOther MaterialsVideo resources:
Server size: 8069 files, 1215Mb (Server statistics)
Project updated by Project sponsored by YUVsoft Corp. Project supported by MSU Graphics & Media Lab |