README.md

---
license: apache-2.0
language:
- en
base_model:
- tencent/HunyuanVideo
pipeline_tag: text-to-video
---

# SkyReels V1: Human-Centric Video Foundation Model
<p align="center">
  <img src="assets/logo2.png" alt="Skyreels Logo" width="60%">
</p>

<p align="center">
<a href="https://github.com/SkyworkAI/SkyReels-V1" target="_blank">🌐 Github</a> · 👋 <a href="https://www.skyreels.ai/home?utm_campaign=huggingface_V1_t2v" target="_blank">Playground</a> · 💬 <a href="https://discord.gg/PwM6NYtccQ" target="_blank">Discord</a>
</p>

---
This repo contains Diffusers-format model weights for SkyReels V1 Text-to-Video models. You can find the inference code on our github repository [SkyReels-V1](https://github.com/SkyworkAI/SkyReels-V1).

## Introduction

SkyReels V1 is the first and most advanced open-source human-centric video foundation model. By fine-tuning <a href="https://huggingface.co/tencent/HunyuanVideo">HunyuanVideo</a> on O(10M) high-quality film and television clips, Skyreels V1 offers three key advantages:

1. **Open-Source Leadership**: Our Text-to-Video model achieves state-of-the-art (SOTA) performance among open-source models, comparable to proprietary models like Kling and Hailuo.
2. **Advanced Facial Animation**: Captures 33 distinct facial expressions with over 400 natural movement combinations, accurately reflecting human emotions.
3. **Cinematic Lighting and Aesthetics**: Trained on high-quality Hollywood-level film and television data, each generated frame exhibits cinematic quality in composition, actor positioning, and camera angles.

## 🔑 Key Features

### 1. Self-Developed Data Cleaning and Annotation Pipeline

Our model is built on a self-developed data cleaning and annotation pipeline, creating a vast dataset of high-quality film, television, and documentary content.

- **Expression Classification**: Categorizes human facial expressions into 33 distinct types.
- **Character Spatial Awareness**: Utilizes 3D human reconstruction technology to understand spatial relationships between multiple people in a video, enabling film-level character positioning.
- **Action Recognition**: Constructs over 400 action semantic units to achieve a precise understanding of human actions.
- **Scene Understanding**: Conducts cross-modal correlation analysis of clothing, scenes, and plots.

### 2. Multi-Stage Image-to-Video Pretraining

Our multi-stage pretraining pipeline, inspired by the <a href="https://huggingface.co/tencent/HunyuanVideo">HunyuanVideo</a> design, consists of the following stages:

- **Stage 1: Model Domain Transfer Pretraining**: We use a large dataset (O(10M) of film and television content) to adapt the text-to-video model to the human-centric video domain.
- **Stage 2: Image-to-Video Model Pretraining**: We convert the text-to-video model from Stage 1 into an image-to-video model by adjusting the conv-in parameters. This new model is then pretrained on the same dataset used in Stage 1.
- **Stage 3: High-Quality Fine-Tuning**: We fine-tune the image-to-video model on a high-quality subset of the original dataset, ensuring superior performance and quality.

## Model Introduction
| Model Name      | Resolution | Video Length | FPS | Download Link |
|-----------------|------------|--------------|-----|---------------|
| SkyReels-V1-Hunyuan-I2V | 544px960p  | 97           | 24  | 🤗 [Download](https://huggingface.co/Skywork/SkyReels-V1-Hunyuan-I2V) |
| SkyReels-V1-Hunyuan-T2V (Current) | 544px960p  | 97           | 24  | 🤗 [Download](https://huggingface.co/Skywork/SkyReels-V1-Hunyuan-T2V) |

## Usage
**See the [Guide](https://github.com/SkyworkAI/SkyReels-V1) for details.**

## Citation
```BibTeX
@misc{SkyReelsV1,
  author = {SkyReels-AI},
  title = {Skyreels V1: Human-Centric Video Foundation Model},
  year = {2025},
  publisher = {Huggingface},
  journal = {Huggingface repository},
  howpublished = {\url{https://huggingface.co/Skywork/SkyReels-V1-Hunyuan-T2V}}
}
```