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facebookresearch/AnimatedDrawingsArchived

0
View on GitHub↗
12,797 stars·1,161 forks·Python·MIT·32 views

AnimatedDrawings

AnimatedDrawings is a system for transforming static 2D drawings of humanoid figures into animated characters. It provides a workflow for character rigging, motion mapping, and scene assembly to turn hand-drawn sketches into moving visual sequences.

The project utilizes a motion retargeting framework to map movement data from motion capture files onto custom character skeletons regardless of their physical proportions. It employs a rigging tool that uses pose estimation to automatically predict joint locations and create digital skeletons, which can be manually refined to improve animation accuracy.

The software covers a broad range of animation production capabilities, including pixel-based image warping to simulate fluid movement, skeleton-aware masking for character segmentation, and a scene composer for combining multiple animated figures with static backgrounds into final video files.

Features

  • Image-to-Video Character Animation - Transforms static images of drawn human figures into moving characters by applying skeletal motion data.
  • Automatic Pose Annotators - Automatically estimates the pose of drawn figures to generate the rigging files needed for animation.
  • Pose Estimation Frameworks - Uses a computer vision model to predict joint locations on a static image for rigging setup.
  • Motion Transfer Animators - Turns static images of hand-drawn human figures into animated characters using motion data.
  • Image Warping Engines - Deforms drawing pixels based on the movement of the rigged skeleton to simulate fluid animation.
  • 2D Skeletal Rigs - Maps a skeletal structure of joint points to a 2D image to define bending and stretching.
  • Animation Retargeting - Translates movement data from source animation files to target skeletons with different proportions.
  • Skeletal Rigging - Provides tools for estimating poses and creating digital skeletons to automate 2D drawing animation.
  • Motion Retargeting - Maps movement from motion capture files to any character regardless of skeleton structure.
  • Manual Mask Refinement - Provides a visual editor to manually correct automated joint predictions and image masks.
  • Skeletal Structure Definitions - Allows the creation of non-standard skeletal structures for figures with extra limbs or quadrupedal bodies.
  • Scene Compositing Tools - Combines multiple animated drawings and custom backgrounds into a final rendered video sequence.
  • Animation Sequence Renderers - Produces animated sequences as interactive windows or video files via local or remote processing.
  • Digital Art Animation Suites - Combines animated hand-drawn characters with background images to produce complete visual scenes.
  • Scene Composition - Combines multiple animated characters and custom background images into a single video scene.
  • Animation Layer Compositing - Organizes animated characters and static backgrounds into hierarchical layers for final video rendering.
  • Pose-Aware Segmentation Masks - Segments characters from backgrounds by creating boundary masks that follow the predicted pose.

Star history

Star history chart for facebookresearch/animateddrawingsStar history chart for facebookresearch/animateddrawings

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does facebookresearch/animateddrawings do?

AnimatedDrawings is a system for transforming static 2D drawings of humanoid figures into animated characters. It provides a workflow for character rigging, motion mapping, and scene assembly to turn hand-drawn sketches into moving visual sequences.

What are the main features of facebookresearch/animateddrawings?

The main features of facebookresearch/animateddrawings are: Image-to-Video Character Animation, Automatic Pose Annotators, Pose Estimation Frameworks, Motion Transfer Animators, Image Warping Engines, 2D Skeletal Rigs, Animation Retargeting, Skeletal Rigging.

Which projects share features with facebookresearch/animateddrawings?

Projects with overlapping indexed features include: godotengine/godot-demo-projects — This repository is a comprehensive collection of functional 2D and 3D demo projects and implementation samples for the… opentoonz/opentoonz — OpenToonz is a professional 2D animation production suite used to create animated sequences through a digital… humanaigc/animateanyone — AnimateAnyone is an appearance-preserving video synthesizer designed for character animation from a single static… antgroup/echomimic_v2 — EchoMimic V2 is an AI video generation pipeline and computer vision animation model designed to produce synthetic… mkocabas/vibe — VIBE is a 3D human pose estimation framework designed to reconstruct human body shapes and poses from video frames. It… auduno/clmtrackr — clmtrackr is a JavaScript computer vision library designed for facial landmark detection and real-time tracking. It…

Projects sharing features with AnimatedDrawings

These projects share indexed features with AnimatedDrawings. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • godotengine/godot-demo-projectsgodotengine avatar

    godotengine/godot-demo-projects

    8,250View on GitHub↗

    This repository is a comprehensive collection of functional 2D and 3D demo projects and implementation samples for the Godot Game Engine. It serves as an interactive tutorial and reference library, providing a working codebase to demonstrate how to apply engine features in real-world scenarios. The collection focuses on practical implementation guides, covering a wide array of technical capabilities from basic engine fundamentals to advanced rendering and scripting techniques. It allows users to study the application of node-based composition, asset pipelines, and game logic through direct ex

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    View on GitHub↗8,250
  • opentoonz/opentoonzopentoonz avatar

    opentoonz/opentoonz

    7,274View on GitHub↗

    OpenToonz is a professional 2D animation production suite used to create animated sequences through a digital pipeline. It functions as a comprehensive animation timing manager and HD animation renderer, coordinating drawing sequences and cinematography using digital exposure sheets. The software is distinguished by a raster-vector hybrid pipeline and a node-based compositing engine for visual effects synthesis. It employs a palette-based color management system that decouples color data from geometry, allowing for global character color adjustments across multiple files without reprocessing

    C++
    View on GitHub↗7,274
  • humanaigc/animateanyoneHumanAIGC avatar

    HumanAIGC/AnimateAnyone

    14,774View on GitHub↗

    AnimateAnyone is an appearance-preserving video synthesizer designed for character animation from a single static image. It functions as a diffusion image-to-video generator that transforms a source image into a high-fidelity video sequence while maintaining consistent character identity, clothing, and visual details across all frames. The system enables video-driven character reenactment by transferring motions, facial expressions, and body movements from a reference video onto a static character. It employs pose-guided video generation to control movement via skeleton keypoints and pose sig

    View on GitHub↗14,774
  • antgroup/echomimic_v2antgroup avatar

    antgroup/echomimic_v2

    4,597View on GitHub↗

    EchoMimic V2 is an AI video generation pipeline and computer vision animation model designed to produce synthetic human animations. It functions as a generative framework that creates semi-body videos by aligning a static reference image with pose movements extracted from a driving video. The system utilizes a diffusion-based generation process combined with latent space compression and a temporal attention mechanism to ensure smooth transitions between frames. It maintains consistent person identity through reference-based encoding and guides spatial placement via pose-driven motion conditio

    Pythonaudio-driven-body-animationaudio-driven-portrait-animationsaudio-driven-talking-face
    View on GitHub↗4,597
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