MSU Video Upscalers Benchmark 2022: Quality Enhancement
The most extensive comparison of video super-resolution (VSR) algorithms by subjective quality
Our benchmark determines the best upscaling methods for increasing video resolution and improving visual quality using our compact yet comprehensive dataset.
Everyone is welcome to participate! Run your favorite super-resolution method on our compact test video and send us the result to see how well it performs. Check the “Submitting” section to learn the details.
Over 3700 People
have participated in the verified pairwise subjective comparison
30 Test Clips
with both camera-shot
and 2D-animated content
41 Upscalers Tested
with both 4× and 2× scaling on video with complex distortion
An Open Visual Comparison
with original high-resolution fragments available for reference
Structural Distortion Maps
with compensated pixel shifts
for easy artifacts detection
Speed/Quality Scatter Plots
and tables with objective metrics
for a comprehensive comparison
What’s new
- November 13th, 2022: Added HGSRCNN and ESRGCNN
- August 28th, 2022: Release of the Benchmark
- November 9th, 2021: Beta-version Release
Introduction
Our benchmark presents the ranking of video upscalers using crowd-sourced subjective comparison. Over 3700 valid participants have selected the most visually appealing upscaling result in many pairwise comparisons.
For evaluating upscaling methods, we also use various metrics (objective quality measures). In addition, we calculate the average FPS (frames per second).
Scroll below for comparison charts, tables, and interactive visual comparisons of upscaling results.
4× Camera-Shot Leaderboards
4× Camera-Shot Visualizations
4× Camera-Shot Charts
4× 2D-Animated Leaderboards
4× 2D-Animated Visualizations
4× 2D-Animated Charts
2× Camera-Shot Leaderboards
2× Camera-Shot Visualizations
2× Camera-Shot Charts
2× 2D-Animated Leaderboards
2× 2D-Animated Visualizations
2× 2D-Animated Charts
Submitting
To add your upscaling method to the benchmark, follow these steps:
1. Download the input |
Download the test video
If your upscaler requires extracting frames,
|
2. Apply your upscaler |
Apply your 2× or 4× upscaling method to the video Configure it for lossless (CRF0/PNG) output, if possible. If your upscaler outputs images, we recommend using this command after upscaling:ffmpeg -i result/frame%04d.png -crf 0 -pix_fmt yuv444p
|
3. Send us the result |
Send video-upscalers-benchmark@videoprocessing.ai
|
If you have any suggestions or questions, please contact us: video-upscalers-benchmark@videoprocessing.ai
Get Notifications About the Updates of This Benchmark
Do you want to be the first to discover the best new upscalers? We can notify you about this benchmark’s updates: simply submit your preferred email address using the form below. We promise not to send you unrelated information.
Further Reading
Check the “Methodology” section to learn how we prepare our dataset.
Check the “Participants” section to learn which upscalers’ implementations we use.
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MSU Benchmark Collection
- MSU Video Upscalers Benchmark 2022
- MSU Video Deblurring Benchmark 2022
- MSU Video Frame Interpolation Benchmark 2022
- MSU HDR Video Reconstruction Benchmark 2022
- MSU Super-Resolution for Video Compression Benchmark 2022
- MSU No-Reference Video Quality Metrics Benchmark 2022
- MSU Full-Reference Video Quality Metrics Benchmark 2022
- MSU Video Alignment and Retrieval Benchmark
- MSU Mobile Video Codecs Benchmark 2021
- MSU Video Super-Resolution Benchmark
- MSU Shot Boundary Detection Benchmark 2020
- MSU Deinterlacer Benchmark
- The VideoMatting Project
- Video Completion
- Codecs Comparisons & Optimization
- VQMT
- MSU Datasets Collection
- Metrics Research
- Video Quality Measurement Tool 3D
- Video Filters
- Other Projects