
TVPaint Animation
The digital solution for your professional 2D animation projects.

Transform static character sketches into rigged 3D-mapped animations using Meta's FAIR computer vision architecture.

Animated Drawings, developed by Meta's Fundamental AI Research (FAIR) team, represents a significant breakthrough in democratization of computer vision. The system utilizes a specialized pipeline consisting of Mask R-CNN for character detection, ResNet-50 for feature extraction, and AlphaPose for 17-point humanoid skeleton mapping. In the 2026 market landscape, it serves as the foundational open-source benchmark for sketch-to-video synthesis. Unlike generative video models that hallucinate frames, Animated Drawings uses precise geometric retargeting to map pre-defined motion capture data onto user-provided masks. This architectural choice ensures that the original artistic intent of the drawing remains intact while enabling fluid movement. The tool is particularly notable for its 'humanoid heuristic' which allows it to interpret varied artistic styles—from stick figures to detailed watercolor characters—as long as a basic anatomical structure is present. By 2026, its integration into educational curricula and creative prototyping workflows has solidified its position as the go-to utility for bridge-level animation tasks where full-scale CGI rigging would be cost-prohibitive.
Animated Drawings, developed by Meta's Fundamental AI Research (FAIR) team, represents a significant breakthrough in democratization of computer vision.
Explore all tools that specialize in remove image backgrounds. This domain focus ensures Animated Drawings delivers optimized results for this specific requirement.
Explore all tools that specialize in pose estimation. This domain focus ensures Animated Drawings delivers optimized results for this specific requirement.
Uses instance segmentation to distinguish the drawn character from the background with pixel-level precision.
Translates Biovision Hierarchy (BVH) files into 2D character deformations.
An algorithmic failsafe that predicts joint locations even if the drawing is missing limbs.
Converts raster drawings into deformable vector-like meshes for smoother animation.
A React-based frontend for manual joint and mask refinement.
Full containerization support for deploying the inference engine locally.
Support for non-humanoid skeletons via modified config files in the open-source version.
Navigate to the Meta Demo Lab web interface or clone the GitHub repository.
Upload a high-contrast drawing of a character on a plain white background.
Review and accept the FAIR Research Data Consent form for model training.
Use the bounding box tool to isolate the character from any peripheral drawing elements.
Review the AI-generated mask; use the pencil and eraser tools to refine character boundaries.
Confirm the 17-point skeletal joint placements (ears, eyes, shoulders, elbows, wrists, hips, knees, ankles).
Manually adjust any misaligned joints to ensure proper rotation axes.
Select from the motion library categories (Dance, Funny, Jumping, Walking).
Preview the animation loop in the browser-based WebGL renderer.
Export the final animation as a MP4 or share via a direct URL link.
All Set
Ready to go
Verified feedback from other users.
"Users praise the simplicity and the 'magic' of seeing their art move, though some note it struggles with non-humanoid shapes (four-legged animals)."
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The digital solution for your professional 2D animation projects.

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