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Subjective MSU Video Codecs Comparison 2020

Video group head:	Dr. Dmitriy Vatolin
Project head:	Dr. Dmitriy Kulikov
Measurements, analysis:	Dr. Mikhail Erofeev, Egor Sklyarov, Nickolay Safonov, Anastasia Antsiferova

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Methodology
- Subjective Comparison Methodology
- Test hardware characteristics
Codecs analysis and tuning for codec developers and codec users
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Summary

Goal: This report presents the results of video codecs comparison using subjective quality measurement.

Main points of this test:

11 codecs of HEVC/AV1/AVC and other standards were evaluated in winter 2020–2021
For subjective quality measurements we used Subjectify.us crowdsourcing platform. We involved more than 6,100 participants

	Offline (1 fps)	Online (30 fps)
Best quality (YUV-Subjective)	1st: BVC2 2nd: Alibaba S265 3rd: KAV1_v2	1st: Alibaba S265 2nd: XCCZM265 3rd: x265
Best speed/quality trade-off (YUV-Subjective)	1st: x264 2nd: QAV1 3rd: SIF Codec	1st: XCCZM265 2nd: SIF Codec

Figure 1 Overall subjective quality — Offline (1 fps)

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Subjective Report Subjective comparison conducted on Subjectify.us platform Released on March, 23	11 codecs Alibaba S265, BVC2, KAV1_v1, KAV1_v2, QAV1, rav1e, Reference x265, SIF Codec, XCCZM265, x264, x265	Free version HTML report (800 KB) PDF & HTML reports (ZIP, 5.3 MB) Enterprise version You will receive enterprise versions of all reports (FullHD, Subjective, 4K and High Quality) Contact us if you want to buy only Enterprise Subjective Report
	6,100+ unique observers 236,736 valid answers
	8 video sequences Short fragments from Xiph, Vimeo, YouTube UGC
	2 Encoding Use Cases Offline (1 fps), Online (30 fps)
	14 metrics Subjective score and 13 objective, including: YUV-SSIM, YUV-PSNR (avg. log), YUV-PSNR (avg. MSE), Y-VMAF (v0.6.3)
	HTML and PDF documents 540+ interactive charts and 69 pages

Participated codecs

	Codec name	Use cases	Standard	Version
1	Alibaba S265 Alibaba Taobao codec Team	Offline (1 fps), Online (30 fps)	HEVC	S265 v5, Windows
2	BVC2 Bytedance Inc.	Offline (1 fps)	Other	V1, Windows
3	KAV1_v1 CKL DXX ZWJ XQQ CC ZHB ZZW	Offline (1 fps)	AV1	8ec71bcc, Windows
4	KAV1_v2 CKL DXX ZWJ XQQ CC ZHB ZZW	Offline (1 fps)	AV1	04ea2aa4, Windows
5	QAV1 iQIYI Inc.	Offline (1 fps)	AV1	Linux
6	rav1e The rav1e contributors	Offline (1 fps)	AV1	Windows
7	Reference x265 MulticoreWare, Inc., presets by MSU	Offline (1 fps), Online (30 fps)	HEVC	Windows
8	SIF Codec SIF Codec LLC	Offline (1 fps), Online (30 fps)	Other	Windows
9	XCCZM265 XCCZM Codec Team	Offline (1 fps), Online (30 fps)	HEVC	Linux
10	x264 x264 project	Offline (1 fps), Online (30 fps)	AVC	Windows
11	x265 MulticoreWare, Inc.	Offline (1 fps), Online (30 fps)	HEVC	Windows

Subjective Comparison Methodology

For subjective quality measurements we used Subjectify.us crowdsourcing platform. We involved more than 6,100 participants. After deleting replies from bots we got 236,736 pairwise answers. Bradley-Terry model was used to compute global rank.

To conduct an online crowdsourced comparison, we uploaded encoded streams to Subjectify.us. For better browser compatibility we performed transcoding with x264 and CRF=16.
The platform hired study participants and showed the upload streams to them in pairs. Each pair consisted of two variants of the same test video sequence encoded by various codecs at various bitrates. Videos from each pair were presented to study participant sequentially (i.e., one after another) in full-screen mode. After viewing each pair, participants were asked to choose the video with the best visual quality. They also had the option to play the videos again or to indicate that the videos have equal visual quality. We assigned each study participant 12 pairs, including 2 hidden quality-control pairs, and each received money reward after successfully completing the task. The quality-control pairs consisted of test videos compressed by the x264 encoder at 1 Mbps and 4 Mbps. Responses from participants who failed to choose the 4 Mbps sequence for one or more quality-control questions were excluded from further consideration.
In total we collected 236,736 valid answers from 6,100+ unique participants. To convert the collected pairwise results to subjective scores, we used the Bradley-Terry model [1]. Thus, each codec run received a quality score. We then linearly interpolated these scores to get continuous rate-distortion (RD) curves, which show the relationship between the real bitrate (i.e., the actual bitrate of the encoded stream) and the quality score. Section “RD Curves” shows these curves.

Test Hardware Characteristics

CPU: Intel Socket 1151 Core i7 8700K (Coffee Lake) (3.7Ghz, 6C12T, TDP 95W)
Mainboard: ASRock Z370M Pro4
RAM: Crucial CT16G4DFD824A 2x16GB (totally 32 GB) DIMM DDR4 2400MHz CL15
OS: Windows 10 x64

Codec Analysis and Tuning for Codec Developers and Codec Users

Computer Graphics and Multimedia Laboratory of Moscow State University:

15+ years working in the area of video codec analysis and tuning using objective quality metrics and subjective comparisons.
27+ reports of video codec comparisons and analysis (H.265, H.264, AV1, VP9, MPEG-4, MPEG-2, decoders' error recovery).
Methods and algorithms for codec comparison and analysis development, separate codec's features and codec's options analysis.

We could perform next tasks for codec developers and codec users.

Strong and Weak Points of Your Codec

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Weak and strong points for your encoder and complete information about encoding quality on different content types.
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Independent Codec Estimation Comparing to Other Codecs for Different Use-cases

Comparative analysis of your encoder and other encoders.
We have direct contact with many codec developers.
You will know place of your encoder between other newest well-known encoders (compare encoding quality, speed, bitrate handling, etc.).

Encoder Features Implementation Optimality Analysis

We 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.

Thanks

Special thanks to the following contributors of our previous comparisons

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Contact Information

compression.ru	in cooperation with	Lomonosov MSU Graphics & Media Lab (Video Group)
		Dubna State University
		Institute for Information Transmission Problems RAS