zai-org/SCAIL

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1053 stars · 60 forks observed · 2026-10-04

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SCAIL is the official inference implementation of a 14B diffusion transformer model that generates studio-grade character animation videos from a reference character image and a driving pose sequence. It uses in-context learning of 3D-consistent pose representations to handle complex motions like turning and flipping with coherent depth-aware motion.

Use cases

• animate a character image from a motion capture or pose video
• generate studio-grade character animation from pose sequences
• drive a static character with complex motions like flips and turns
• video-to-video character reenactment with 3D-consistent poses
• produce production-quality animated character videos without a studio pipeline
• research controllable video generation with pose conditioning

When to choose

• you need high-fidelity character animation driven by pose input
• your motions involve complex body rotation, flipping, or turning that simpler pose-guided models fail on
• you want to run inference with a pretrained 14B character animation model on GPU
• you are researching pose representation and conditioning for video diffusion models

When to avoid

• you lack a high-VRAM GPU to run a 14B diffusion transformer
• you need training or fine-tuning code rather than inference
• you need real-time or low-latency animation
• you want lightweight 2D skeletal animation for games rather than generated video

Facets

library · maturity active

video-processing machine-learning deep-learning llm-inference artificial-intelligence computer-vision deep-learning python character-animation video-generation video2video pose-driven-animation diffusion-transformer cvpr-2026 in-context-learning 3d-pose-representation image-to-video research-model video gpu linux

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