Awesome GitHub RepositoriesMotion Vector Calculation

This project is an educational suite and technical guide designed for mastering video codecs and signal processing. It provides a structured curriculum through an engineering course, interactive labs, and tutorials focused on the fundamental principles of video compression and digital signal processing. The resource includes a technical guide for analyzing specific codecs like AV1, VP9, and H.265. It distinguishes itself by providing a containerized media lab, which ensures a consistent development environment for experimenting with video technology tools and notebooks. The project covers a

This project is an open-source 3D game engine designed for building high-fidelity games, simulations, and cinematic environments. It functions as a robotics simulation platform with native integration for ROS 2 to model robot controllers and sensors. The engine features a multi-threaded Forward+ physically based renderer that supports hardware-accelerated ray tracing and global illumination. The system is built on a modular extension architecture using Gems to add or replace features without modifying core binaries. It includes a native SDK for AWS cloud integration, enabling IAM authenticati

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

jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

SAMURAI is a zero-shot visual tracking model that adapts the Segment Anything architecture for video object segmentation. It uses a first-frame prompt, such as a bounding box or mask, to initialize tracking, then employs a motion-aware memory mechanism that stores and updates temporal motion features across frames to guide mask refinement. An online memory update strategy continuously refreshes this memory with new frame predictions, while temporal motion encoding computes optical flow between consecutive frames to inform object boundary and occlusion handling. The system is designed for real

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

OpenCVSharp is a .NET library that wraps native OpenCV functions, providing C# developers with access to OpenCV's computer vision capabilities through an API that mirrors the native C/C++ style. It serves as a managed wrapper for image processing, feature detection, object detection, and image manipulation tasks, while also handling automatic disposal of unmanaged OpenCV resources like Mat objects to prevent memory leaks in .NET applications. The library enables keypoint detection and descriptor extraction using algorithms such as AKAZE, BRISK, or FAST, with brute-force or FLANN-based matchin

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

AniPortrait is an AI video synthesis pipeline designed to generate photorealistic speaking portraits and facial animations. It functions as a talking head generator and audio-driven animator that synchronizes lip movements, expressions, and head poses to speech or reference video sources. The system includes a facial expression transfer tool for reenacting movements from a source video onto a static reference image. It utilizes a latent diffusion model with reference-based image conditioning to maintain visual identity and consistency across generated frames. The pipeline covers audio-to-exp

MathUtilities ist eine Sammlung spezialisierter Toolkits, die Engines für Geometrie, Computer Vision, Mathematik, Physiksimulation und Signalverarbeitung bereitstellen. Sie fungiert als umfassende Mathematik- und Physikbibliothek mit Fokus auf lineare Algebra, numerische Optimierung und geometrische Berechnungen für technische Anwendungen. Das Projekt zeichnet sich durch ein Physiksimulations-Toolkit und eine 3D-Geometrie-Engine aus. Diese bieten Funktionen für Verlet-Integration, iterative Inverse-Kinematik-Solver, Distance-Field-Rendering mittels volumetrischem Raymarching und Mesh-Geometrie-Deformation. Es enthält zudem ein Computer-Vision-Dienstprogramm zur Schätzung der relativen Kamerabewegung und zur Generierung von Fisheye-Projektionen. Die Bibliothek deckt breite Funktionsbereiche ab, darunter Kollisionserkennungssysteme mittels Minkowski-Differenzen und Spatial Hashing, Robotik-Bewegungsplanung und Signalverarbeitung zur Rauschunterdrückung mittels Kalman-Filtern. Zusätzliche Funktionen umfassen numerische Datenoptimierung, Operationen der linearen Algebra für Point-Set-Fitting und reflexionsbasierte JSON-Serialisierung für Objekthierarchien.

Auto-editor ist ein automatisierter Video-Editor für die Befehlszeile, der FFmpeg verwendet, um Stille und inaktive Aufnahmen aus Videodateien zu entfernen. Er fungiert als Verarbeitungssuite mit spezialisierten Schnitt-Generatoren, die Segmente basierend auf Lautstärkeschwellen, Bewegungsanalyse und Speech-to-Text-Transkription zum Trimmen identifizieren. Das Tool zeichnet sich durch einen flexiblen Post-Production-Workflow aus, der es Benutzern ermöglicht, automatisierte Schnitt-Timelines als XML- oder JSON-Dateien für die Verwendung in professioneller nicht-linearer Schnittsoftware zu exportieren. Über das einfache Löschen hinaus kann es dynamische Wiedergabeanpassungen vornehmen, wie z. B. die Geschwindigkeit leiser Segmente zu erhöhen, anstatt sie vollständig zu entfernen. Das Projekt deckt ein breites Spektrum an Medienmanipulationsfunktionen ab, darunter Audio-Normalisierung, Sibilanz-Reduzierung und visuelle Effekte wie Layer-Compositing, Grafik-Overlays und Skalierungstransformationen. Es unterstützt zudem das Einlesen von Remote-Medien über URLs und bietet Dienstprogramme zur Vorschau von Schnittstatistiken, ohne das finale Video zu rendern.

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

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

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

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