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9 个仓库

Awesome GitHub RepositoriesMotion-Based Frame Interpolation

Uses motion estimation to generate intermediate frames for smooth motion at the cost of high computation.

Distinct from Motion Vector Calculation: Distinct from Motion Vector Calculation: focuses on generating new frames from motion vectors rather than just calculating them.

Explore 9 awesome GitHub repositories matching graphics & multimedia · Motion-Based Frame Interpolation. Refine with filters or upvote what's useful.

Awesome Motion-Based Frame Interpolation GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • yemount/pose-animatoryemount 的头像

    yemount/pose-animator

    8,843在 GitHub 上查看↗

    Pose-animator is a system that maps real-time body and face tracking data to 2D vector illustrations. It functions as a skeletal animation engine and motion controller that translates human keypoint recognition into instantaneous SVG path updates. The project enables real-time motion capture from webcam feeds and pose extraction from static images. It utilizes a skeletal rig to link virtual bones to vector character surfaces, allowing for the animation of custom characters and interactive avatars. The tool incorporates client-side machine learning inference for processing camera frames, coor

    Smooths the transitions between disparate ML detection results to prevent jittering in character motion.

    JavaScript
    在 GitHub 上查看↗8,843
  • hvision-nku/storydiffusionHVision-NKU 的头像

    HVision-NKU/StoryDiffusion

    6,430在 GitHub 上查看↗

    StoryDiffusion is a generative AI system designed for consistent character image and video generation. It utilizes a pluggable cross-attention module to inject shared character representations into pretrained diffusion models, allowing for visual identity stability across multiple images and scenes without retraining the base model. The project features a video generation pipeline that produces temporally coherent sequences from text prompts or condition images. It employs a latent space motion interpolator to predict intermediate frames and semantic motion, enabling long-range video generati

    Generates intermediate video frames by interpolating semantic data within a variational autoencoder.

    Jupyter Notebook
    在 GitHub 上查看↗6,430
  • hooke007/mpv_playkithooke007 的头像

    hooke007/mpv_PlayKit

    6,473在 GitHub 上查看↗

    Uses motion estimation to generate intermediate frames for smooth video playback.

    GLSLmpvmpv-configmpv-player
    在 GitHub 上查看↗6,473
  • doubiiu/tooncrafterDoubiiu 的头像

    Doubiiu/ToonCrafter

    5,972在 GitHub 上查看↗

    ToonCrafter is a model that combines latent diffusion, reference-based colorization, and sketch-guided control for cartoon animation and interpolation. It functions as a cartoon video interpolation model, a reference-based colorization model, and a sketch-guided animation tool, all built on a latent diffusion animation framework. The project distinguishes itself by integrating three core capabilities into a single pipeline: generating smooth intermediate frames between two cartoon images using diffusion-based priors, transferring color and style from a reference image onto black-and-white ske

    Leverages diffusion priors to create temporally coherent intermediate frames for cartoon animation.

    Python
    在 GitHub 上查看↗5,972
  • zejun-yang/aniportraitZejun-Yang 的头像

    Zejun-Yang/AniPortrait

    5,020在 GitHub 上查看↗

    AniPortrait 是一个 AI 视频合成流水线,旨在生成照片级逼真的说话肖像和面部动画。它充当说话头像生成器和音频驱动的动画师,将唇部动作、表情和头部姿势与语音或参考视频源同步。 该系统包括一个面部表情迁移工具,用于将源视频中的动作重演到静态参考图像上。它利用带有参考图像调节的潜在扩散模型,在生成的帧中保持视觉身份和一致性。 该流水线涵盖音频到表情的映射、姿势引导的运动控制和照片级逼真的视频合成。它结合了帧插值上采样,以加速生成过程并减少总渲染时间。

    Uses latent space interpolation to generate intermediate frames for smoother video and faster rendering.

    Python
    在 GitHub 上查看↗5,020
  • pancaketas/lsfg-vkPancakeTAS 的头像

    PancakeTAS/lsfg-vk

    4,097在 GitHub 上查看↗

    lsfg-vk is a Vulkan-based frame generation tool and graphics middleware designed to increase perceived frame rates in graphics applications. It implements a lossless scaling algorithm to insert generated frames between rendered ones, increasing motion smoothness without reducing image quality. The project features a dedicated programming interface for integrating frame generation logic into external applications and includes an application profile manager. This manager allows specific generation settings to be assigned to individual executables, automating configuration upon application start

    Uses Vulkan-based motion vector analysis and pixel data to generate intermediate frames for smoother motion.

    C++frame-generationlinuxlosslessscaling
    在 GitHub 上查看↗4,097
  • djdefrag/qualityscalerDjdefrag 的头像

    Djdefrag/QualityScaler

    2,970在 GitHub 上查看↗

    QualityScaler is an AI video upscaler and local media processing tool designed to increase the resolution and visual quality of videos and images. It uses deep learning models to enhance detail and remove noise, operating as an offline application that executes all computations on local hardware. The project functions as a GPU-accelerated media processor that distributes workloads across multiple graphics cards to increase rendering speed. To prevent memory overflow during high-resolution tasks, it employs a tiled image processing method that splits large assets into smaller sections. The sy

    Implements motion-based frame interpolation to blend original and upscaled frames for smoother transitions.

    Pythonamdanimecompression-artifact-reduction
    在 GitHub 上查看↗2,970
  • tntwise/real-video-enhancerTNTwise 的头像

    TNTwise/REAL-Video-Enhancer

    2,137在 GitHub 上查看↗

    Real-Video-Enhancer is a cross-platform desktop application that utilizes neural networks to upscale resolution, generate intermediate frames, and denoise video files. It functions as a deep learning video processor that runs restoration models through hardware acceleration, dispatching heavy prediction workloads directly to underlying graphics hardware. The software executes optical-flow-based frame interpolation to increase framerates and motion smoothness, alongside dedicated filtering models that remove digital noise and blocky compression artifacts from compressed video streams. Additio

    Generates intermediate video frames using motion estimation and neural interpolation models to increase framerate and smoothness.

    Pythonguiinterpolationlinux
    在 GitHub 上查看↗2,137
  • dexplo/bar_chart_racedexplo 的头像

    dexplo/bar_chart_race

    1,452在 GitHub 上查看↗

    Bar chart race is a Python data visualization library that transforms ordered tabular time-series data into animated bar and line chart races. It operates as an extension for rendering dynamic charts that illustrate how rankings and values change over time. The library interpolates wide-format chronological tables into densely sampled frame sequences, calculating intermediate numeric values to produce fluid motion animations. It orchestrates iterative canvas redraws through a plotting backend while supporting external multimedia encoders to export compressed standard video files. Generated a

    Calculates intermediate numeric bar lengths between discrete time periods using linear interpolation to produce fluid motion.

    Python
    在 GitHub 上查看↗1,452
  1. Home
  2. Graphics & Multimedia
  3. Motion Vector Calculation
  4. Motion-Based Frame Interpolation

探索子标签

  • Latent Frame Interpolators1 个子标签Generating intermediate video frames by interpolating data within a latent space. **Distinct from Motion-Based Frame Interpolation:** Operates on semantic latent data rather than calculating pixel-based motion vectors.