thu-ml/Causal-Forcing
Official codebase for "Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation"
This project helps video creators, animators, and content producers generate high-quality, real-time videos from text descriptions or a single image. You provide text prompts or an initial image, and it outputs dynamic video clips with improved visual quality and motion. It's designed for professionals who need efficient, high-fidelity video generation.
456 stars.
Use this if you need to quickly create visually rich and fluid video content from text prompts or an initial image, especially for applications requiring real-time performance.
Not ideal if your primary need is for generating videos longer than a few seconds (81 frames) without additional extensions.
Stars
456
Forks
21
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/thu-ml/Causal-Forcing"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
PRIS-CV/DemoFusion
Let us democratise high-resolution generation! (CVPR 2024)
mit-han-lab/distrifuser
[CVPR 2024 Highlight] DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models
Tencent-Hunyuan/HunyuanPortrait
[CVPR-2025] The official code of HunyuanPortrait: Implicit Condition Control for Enhanced...
giuvecchio/matfuse
MatFuse: Controllable Material Generation with Diffusion Models (CVPR2024)
Shilin-LU/TF-ICON
[ICCV 2023] "TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition" (Official...