16 repository-uri
Computing the per-pixel movement between frames to support temporal rendering effects.
Distinct from Motion Blur Simulations: Different from general motion blur; it is the underlying calculation of vectors for TAA and blur.
Explore 16 awesome GitHub repositories matching graphics & multimedia · Motion Vector Calculation. Refine with filters or upvote what's useful.
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
Identifies and encodes changes between sequential video frames using block motion compensation and motion vectors.
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
Computes frame position differences in shaders to enable motion blur and temporal anti-aliasing.
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.
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
Calculates relative pixel motion between frames using dedicated GPU hardware to track object movement.
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
Computes optical flow between consecutive frames to inform object boundary and occlusion handling.
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.
Uses motion estimation to generate intermediate frames for smooth video playback.
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
Implements dense optical flow estimation using the Brox variational method for motion analysis.
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
Generates intermediate cartoon frames by interpolating data within a compressed latent space.
AniPortrait este un pipeline de sinteză video AI conceput pentru a genera portrete vorbitoare fotorealiste și animații faciale. Funcționează ca un generator de talking head și animator bazat pe audio care sincronizează mișcările buzelor, expresiile și pozițiile capului cu surse de vorbire sau video de referință. Sistemul include un instrument de transfer al expresiilor faciale pentru reenactment-ul mișcărilor dintr-un video sursă pe o imagine de referință statică. Utilizează un model de difuzie latentă cu condiționare a imaginii bazată pe referință pentru a menține identitatea vizuală și consistența pe cadrele generate. Pipeline-ul acoperă maparea audio-la-expresie, controlul mișcării ghidat de poziție și sinteza video fotorealistă. Încorporează upsampling prin interpolarea cadrelor pentru a accelera procesul de generare și a reduce timpul total de randare.
Uses latent space interpolation to generate intermediate frames for smoother video and faster rendering.
MathUtilities este o colecție de toolkit-uri specializate care oferă motoare pentru geometrie, viziune artificială, matematică, simulare fizică și procesarea semnalelor. Funcționează ca o bibliotecă cuprinzătoare de matematică și fizică axată pe algebră liniară, optimizare numerică și calcule geometrice pentru aplicații tehnice. Proiectul se distinge printr-un toolkit de simulare fizică și un motor de geometrie 3D. Acestea oferă capabilități pentru integrare Verlet, solvere iterative de cinematică inversă, randare de câmpuri de distanță prin raymarching volumetric și deformarea geometriei mesh-urilor. Include, de asemenea, un utilitar de viziune artificială pentru estimarea mișcării relative a camerei și generarea de proiecții fisheye. Biblioteca acoperă arii largi de capabilități, inclusiv sisteme de detectare a coliziunilor folosind diferențe Minkowski și hashing spațial, planificarea mișcării în robotică și procesarea semnalelor pentru reducerea zgomotului folosind filtre Kalman. Funcționalitatea suplimentară include optimizarea datelor numerice, operații de algebră liniară pentru potrivirea seturilor de puncte și serializare JSON bazată pe reflexie pentru ierarhiile de obiecte.
Solves for the relative motion between two images by tracking the movement of feature points.
Auto-editor este un editor video automatizat pentru linia de comandă care utilizează FFmpeg pentru a elimina tăcerea și filmările inactive din fișierele video. Funcționează ca o suită de procesare cu generatoare de tăieturi specializate care identifică segmentele de tăiat pe baza pragurilor de volum, analizei mișcării și transcrierii speech-to-text. Instrumentul se distinge prin oferirea unui flux de lucru flexibil de post-producție, permițând utilizatorilor să exporte timeline-uri de tăiere automatizate ca fișiere XML sau JSON pentru utilizare în software-uri profesionale de editare non-liniară. Dincolo de simpla ștergere, poate efectua ajustări dinamice de redare, cum ar fi creșterea vitezei segmentelor silențioase în loc să le elimine complet. Proiectul acoperă o gamă largă de capabilități de manipulare media, inclusiv normalizarea audio, reducerea sibilanței și efecte vizuale precum compoziția de straturi, suprapuneri grafice și transformări de scalare. De asemenea, suportă ingestia de media la distanță prin URL-uri și oferă utilitare pentru a previzualiza statisticile editării fără a randa videoclipul final.
Detects still footage by measuring pixel-level changes between frames to identify sections with minimal movement.
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.
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.
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.
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.