MSU Video Frame Interpolation Benchmark
Discover the best algorithm to make high-quality and smooth slow motion videos
Konstantin Kozhemiakov
Key features of the Benchmark
- Comparison of 8 methods of video frame interpolation
- A new dataset with gaming content and real-life footage
- 5 objective metrics for interpolation quality assessment and speed measurement of algorithms
- Subjective comparison with more than 400 participants (powered by Subjectify.us)
Leaderboard
The table below shows a comparison of all Video Frame Interpolation methods.
You can sort the table by a specific metric.
To walk through papers and implementations of algorithms go to the Participants tab.
Discover details of the comparison in the Methodology tab.
Dataset:
Rank | Algorithm | Subjective | PSNR | SSIM | VMAF | LPIPS | MS-SSIM | FPS |
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* these algorithms do not require computing power
Charts
Speed/Quality trade-off
Metric: Test:
Visualizations
This section presents visualizations of all algorithms.
- The first line is full-sized frames
- The second line is crops from interpolated intermediate frames
- The third and fourth lines are the visualizations of error maps of PSNR and SSIM respectively.
Video:
Model 1: Model 2: Model 3:
Drag a red rectangle in the area, which you want to crop.
GT



GT

RIFE

CAIN

Your method submission
Verify the interpolation ability of your Video Frame Interpolation algorithm and compare it with other solutions. You can see information about other participants here.
1. Download input data
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Download low frame rate videos |
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2. Apply your algorithm |
Interpolate intermediate frames of low FPS videos using your algorithm. You can also send us the code of your method or the executable file and we will run it ourselves. |
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3. Send us result |
Send us an email to vfi-benchmark@videoprocessing.ai
with the following information:
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Contacts
We would highly appreciate any suggestions and ideas on how to improve our benchmark. For questions and propositions, please contact us: vfi-benchmark@videoprocessing.ai
Also you can subscribe to updates on our benchmark:
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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