README.md

---
title: stable-virtual-camera
app_file: demo_gr.py
sdk: gradio
sdk_version: 5.20.1
---
# Stable Virtual Camera

<a href="https://stable-virtual-camera.github.io"><img src="https://img.shields.io/badge/%F0%9F%8F%A0%20Project%20Page-gray.svg"></a>
<a href="http://arxiv.org/abs/2503.14489"><img src="https://img.shields.io/badge/%F0%9F%93%84%20arXiv-2503.14489-B31B1B.svg"></a>
<a href="https://stability.ai/news/introducing-stable-virtual-camera-multi-view-video-generation-with-3d-camera-control"><img src="https://img.shields.io/badge/%F0%9F%93%83%20Blog-Stability%20AI-orange.svg"></a>
<a href="https://huggingface.co/stabilityai/stable-virtual-camera"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Model_Card-Huggingface-orange"></a>
<a href="https://huggingface.co/spaces/stabilityai/stable-virtual-camera"><img src="https://img.shields.io/badge/%F0%9F%9A%80%20Gradio%20Demo-Huggingface-orange"></a>
<a href="https://www.youtube.com/channel/UCLLlVDcS7nNenT_zzO3OPxQ"><img src="https://img.shields.io/badge/%F0%9F%8E%AC%20Video-YouTube-orange"></a>

`Stable Virtual Camera (Seva)` is a 1.3B generalist diffusion model for Novel View Synthesis (NVS), generating 3D consistent novel views of a scene, given any number of input views and target cameras.

# :tada: News

- March 2025 - `Stable Virtual Camera` is out everywhere.

# :wrench: Installation

```bash
git clone --recursive https://github.com/Stability-AI/stable-virtual-camera
cd stable-virtual-camera
pip install -e .
```

Please note that you will need `python>=3.10` and `torch>=2.6.0`.

Check [INSTALL.md](docs/INSTALL.md) for other dependencies if you want to use our demos or develop from this repo.
For windows users, please use WSL as flash attention isn't supported on native Windows [yet](https://github.com/pytorch/pytorch/issues/108175).

# :open_book: Usage

You need to properly authenticate with Hugging Face to download our model weights. Once set up, our code will handle it automatically at your first run. You can authenticate by running

```bash
# This will prompt you to enter your Hugging Face credentials.
huggingface-cli login
```

Once authenticated, go to our model card [here](https://huggingface.co/stabilityai/stable-virtual-camera) and enter your information for access.

We provide two demos for you to interative with `Stable Virtual Camera`.

### :rocket: Gradio demo

This gradio demo is a GUI interface that requires no expertised knowledge, suitable for general users. Simply run

```bash
python demo_gr.py
```

For a more detailed guide, follow [GR_USAGE.md](docs/GR_USAGE.md).

### :computer: CLI demo

This cli demo allows you to pass in more options and control the model in a fine-grained way, suitable for power users and academic researchers. An examplar command line looks as simple as

```bash
python demo.py --data_path <data_path> [additional arguments]
```

For a more detailed guide, follow [CLI_USAGE.md](docs/CLI_USAGE.md).

For users interested in benchmarking NVS models using command lines, check [`benchmark`](benchmark/) containing the details about scenes, splits, and input/target views we reported in the <a href="http://arxiv.org/abs/2503.14489">paper</a>.

# :books: Citing

If you find this repository useful, please consider giving a star :star: and citation.

```
@article{zhou2025stable,
    title={Stable Virtual Camera: Generative View Synthesis with Diffusion Models},
    author={Jensen (Jinghao) Zhou and Hang Gao and Vikram Voleti and Aaryaman Vasishta and Chun-Han Yao and Mark Boss and
    Philip Torr and Christian Rupprecht and Varun Jampani
    },
    journal={arXiv preprint},
    year={2025}
}
```