k4yt3x

    k4yt3x/video2x

    #110 this week

    A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018.

    machine-learning
    deep-learning
    graphics
    anime4k
    frame-interpolation
    neural-networks
    realcugan
    realesrgan
    C++
    AGPL-3.0
    22.1K stars
    1.9K forks
    22.1K GitHub watchers
    Updated Oct 9, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    Ranks #110 of 2,841 repositories GStars tracks this week (top 4%).

    No releases in the last 90 days; the most recent was 622 days ago, with 24 contributors on GitHub.

    Use Cases & Benefits

    • Provides a machine learning-based framework for video super resolution and frame interpolation using C++.
    • Delivers faster, more efficient, and higher quality video upscaling with cross-platform support and Vulkan acceleration.
    • Use for enhancing low-resolution anime videos to 4K quality with Anime4K and Real-ESRGAN models.
    • Use for creating smooth slow-motion videos by interpolating frames with RIFE neural network models.
    • Use for integrating video upscaling and interpolation into cross-platform desktop applications with a user-friendly GUI.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    AGPL 3.0

    Network copyleft: like the GPL, and also triggered by offering the software over a network.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    • AGPL-style copyleft also applies when the software is offered over a network.
    • No commits in the last six months (last push Mar 2026).

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Your system must meet the minimum hardware requirements below to run Video2X.

    Video2X packages are available for the Linux distros listed below. A universal AppImage is also available for other distros. If you'd like to build it from source code, refer to the PKGBUILD file for a general overview of the required dependencies and commands.

    Excerpt from the k4yt3x/video2x README on GitHub (AGPL-3.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Forks

    1.9K+141

    Open issues

    134+12

    Compared with peers in Machine Learning

    Fastest-growing repositories GStars tracks in this cohort for the week of Oct 4, by 7-day star growth

    k4yt3x/video2x compared with Machine Learning repositories by stars, 7-day star growth, health score and last release
    RepositoryStars+7dHealthLast release
    rohitg00/ai-engineering-from-scratch68.7K+3.5K753 days ago
    pytorch/pytorch104.9K+4227513 days ago
    netdata/netdata80.8K+98757 days ago
    roboflow/supervision51.2K+0751 day ago
    paperless-ngx/paperless-ngx46.5K+0654 days ago
    k4yt3x/video2x22.1K+075622 days ago
    Category median68.7K+9875—

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