Before today’s wave of large open video models, VideoCrafter was one of the projects that made open text-to-video generation practical to experiment with. The repository from Tencent AI Lab’s CVC team still hosts both generations of the model, and with more than 5,000 stars it remains a common reference point for video diffusion research.
| Repository | AILab-CVC/VideoCrafter |
| Maintainer | AILab-CVC |
| Primary language | Python |
| GitHub stars | 5,076 (as of 15 September 2026) |
| Last push | 9 January 2026 |
| License status | Research/non-commercial restrictions |
What it does
The README describes VideoCrafter as an open-source toolbox for generating and editing video, currently with text-to-video and image-to-video models. The published checkpoints:
| Model | Task | Resolution |
|---|---|---|
| VideoCrafter2 | Text-to-video | 320×512 |
| VideoCrafter1 | Text-to-video | 576×1024 and 320×512 |
| VideoCrafter1 | Image-to-video | 640×1024 and 320×512 |
VideoCrafter2, released in January 2024, is presented in its technical report as improving motion and concept combination over VideoCrafter1 despite limited training data. For image-to-video, the README now steers users to the team’s separate DynamiCrafter project for higher resolution and better dynamics.
Who it’s for
- Researchers who need an established open baseline for video diffusion.
- Learners who want a smaller, well-documented video model to study before moving to larger ones.
Getting started
The README recommends an Anaconda environment with Python 3.8.5 and pip install -r requirements.txt. Download a checkpoint from Hugging Face into the expected folder (for example checkpoints/base_512_v2/model.ckpt for VideoCrafter2), then run sh scripts/run_text2video.sh or sh scripts/run_image2video.sh. With both models downloaded, python gradio_app.py starts a local demo. No GPU memory requirement is documented.
License status
Checked October 17, 2026: The repository license file includes Apache-style terms with an additional clause limiting the code to research and non-commercial activities. It should not be presented as plain Apache-2.0 or as unrestricted commercial open source. Model checkpoints and optional dependencies must also be checked separately.
Limitations and open questions
- The newest listed checkpoint is from February 2024. By 2026 standards, 320×512 output is low resolution.
- The pinned Python 3.8.5 environment is dated.
- 74 open issues as of 15 September 2026.
- We have not run the models; the sample prompts in the README are the maintainers’ showcase, not our tests.
Sources
- GitHub repository and README
- License file
- AILab-CVC GitHub organisation (profile: “Tencent AI Lab – Computer Vision Center”)
- VideoCrafter2 technical report (arXiv 2401.09047)
- VideoCrafter1 technical report (arXiv 2310.19512)
Related: HunyuanVideo-1.5, a newer open video model · Video Generation.
This profile was drafted with AI assistance from the project’s public repository and reviewed by The Signal’s editors before publication. See our AI Disclosure.
