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license: apache-2.0
tags:
- vae
- video
- image
- autoencoder
- 3d-convolution
library_name: image-video-vae
---
# Image-Video-VAE
3D Convolutional VAE for encoding and decoding both images and video, trained from scratch by Linum AI. [Read the blog post](https://www.linum.ai/field-notes/vae-reconstruction-vs-generation).
## Model Description
A 346.6M parameter 3D convolutional autoencoder that compresses images and video into a compact latent space.
| Property | Value |
|----------|-------|
| Spatial compression | 8x |
| Temporal compression | 4x |
| Latent channels | 16 |
| Parameters | 346.6M (170.1M encoder, 176.5M decoder) |
## Quick Start
**Full documentation: [GitHub - Linum-AI/image-video-vae](https://github.com/Linum-AI/image-video-vae)**
```bash
git clone https://github.com/Linum-AI/image-video-vae.git
cd image-video-vae
uv sync
uv run python encode_decode.py --mode image --input examples/images/original/camel_closeup.jpg
```
Weights are downloaded automatically on first run (~1.3GB).
## Examples
### Image
```bash
uv run python encode_decode.py \
--mode image \
--input examples/images/original/camel_closeup.jpg
```

### Video
```bash
uv run python encode_decode.py \
--mode video \
--input examples/videos/original/woman_in_breeze.mp4
```
<video src="https://huggingface.co/Linum-AI/image-video-vae/resolve/main/examples/woman_in_breeze.mp4" controls autoplay muted loop width="100%"></video>
## Files
```
└── vae.safetensors # VAE model weights (1.3GB)
```
## License
[Apache 2.0](LICENSE)
## Citation
```bibtex
@online{image_video_vae_2026,
title = {VAE: Reconstruction vs. Generation},
author = {Linum AI},
year = {2026},
url = {https://www.linum.ai/field-notes/vae-reconstruction-vs-generation}
}
```
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