Video Upscalers Benchmark: Quality Enhancement

The most extensive comparison of video super-resolution (VSR) algorithms by subjective quality

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G&M Lab head: Dr. Dmitriy Vatolin
Measurements, analysis: 
Nikolai Karetin,
Ivan Molodetskikh

Our benchmark determines the best upscaling methods for increasing video resolution and improving visual quality using our compact yet comprehensive dataset.

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

  • April 9th, 2023: Added LESRCNN, CFSRCNN and ACNet
  • 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

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Further Reading

Check the “Methodology” section to learn how we prepare our dataset.

Check the “Participants” section to learn which upscalers’ implementations we use.

MSU Video Quality Measurement Tool

              

    The tool for performing video/image quality analyses using reference or no-reference metrics

Widest Range of Metrics & Formats

  • Modern & Classical Metrics SSIM, MS-SSIM, PSNR, VMAF and 10+ more
  • Non-reference analysis & video characteristics
    Blurring, Blocking, Noise, Scene change detection, NIQE and more

Fastest Video Quality Measurement

  • GPU support
    Up to 11.7x faster calculation of metrics with GPU
  • Real-time measure
  • Unlimited file size

  • Main MSU VQMT page on compression.ru

Crowd-sourced subjective
quality evaluation platform

  • Conduct comparison of video codecs and/or encoding parameters

What is it?

Subjectify.us is a web platform for conducting fast crowd-sourced subjective comparisons.

The service is designed for the comparison of images, video, and sound processing methods.

Main features

  • Pairwise comparison
  • Detailed report
  • Providing all of the raw data
  • Filtering out answers from cheating respondents

  • Subjectify.us
09 Apr 2023
See Also
PSNR and SSIM: application areas and criticism
Learn about limits and applicability of the most popular metrics
Video Colorization Benchmark
Explore the best video colorization algorithms
Video Saliency Prediction Benchmark
Explore the best video saliency prediction (VSP) algorithms
LEHA-CVQAD Video Quality Metrics Benchmark
Explore newest Full- and No-Reference Video Quality Metrics and find the most appropriate for you.
Learning-Based Image Compression Benchmark
The First extensive comparison of Learned Image Compression algorithms
Super-Resolution for Video Compression Benchmark
Learn about the best SR methods for compressed videos and choose the best model to use with your codec
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