Instructions to use H-oliday/SwiftVR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use H-oliday/SwiftVR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("H-oliday/SwiftVR", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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<p>
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<a href="https://arxiv.org/abs/2606.09516"><img src="https://img.shields.io/badge/arXiv-2606.09516-b31b1b.svg?style=flat-square" alt="arXiv"></a>
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<a href="https://github.
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<a href="https://github.com/H-oliday/SwiftVR">
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<img src="https://img.shields.io/badge/GitHub-Code-181717.svg?style=flat-square&logo=github" alt="GitHub">
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</a>
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</p>
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## Updates
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## 🛠 Installation
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```bash
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git clone https://github.com/
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cd SwiftVR
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conda create -n swiftvr python=3.10 -y
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```python
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from swiftvr import SwiftVRPipeline
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pipe = SwiftVRPipeline.from_pretrained("
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pipe.restore_video("low_quality.mp4", "restored.mp4", upscale=4)
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```
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Unless required by applicable law or agreed to in writing, this project is distributed on an **"AS IS" BASIS**, without warranties or conditions of any kind, either express or implied. See the [LICENSE](./LICENSE) file for the full license text.
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## Contact
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<p>
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<a href="https://arxiv.org/abs/2606.09516"><img src="https://img.shields.io/badge/arXiv-2606.09516-b31b1b.svg?style=flat-square" alt="arXiv"></a>
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<a href="https://h-oliday.github.io/SwiftVR/"><img src="https://img.shields.io/badge/Project-Page-1f8acb.svg?style=flat-square" alt="Project Page"></a>
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<a href="https://github.com/H-oliday/SwiftVR">
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<img src="https://img.shields.io/badge/GitHub-Code-181717.svg?style=flat-square&logo=github" alt="GitHub">
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</a>
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</p>
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SwiftVR is a streaming one-step generative video restoration (VR) framework presented in [SwiftVR: Real-Time One-Step Generative Video Restoration](https://arxiv.org/abs/2606.09516).
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## Updates
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## 🛠 Installation
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```bash
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git clone https://github.com/H-oliday/SwiftVR.git
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cd SwiftVR
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conda create -n swiftvr python=3.10 -y
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```python
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from swiftvr import SwiftVRPipeline
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pipe = SwiftVRPipeline.from_pretrained("H-oliday/SwiftVR").to("cuda", dtype="bfloat16")
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pipe.restore_video("low_quality.mp4", "restored.mp4", upscale=4)
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```
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Unless required by applicable law or agreed to in writing, this project is distributed on an **"AS IS" BASIS**, without warranties or conditions of any kind, either express or implied. See the [LICENSE](./LICENSE) file for the full license text.
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## 📜 Citation
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```bibtex
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@article{yan2026swiftvr,
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title={SwiftVR: Real-Time One-Step Generative Video Restoration},
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author={Yan, Jiaqi and Chen, Xiangyu and Zhong, Xinlin and Huang, Haibin and Zhang, Chi and Liu, Jie and Zhou, Jiantao and Li, Xuelong},
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journal={arXiv preprint arXiv:2606.09516},
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year={2026}
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}
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```
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## Contact
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