EasyRef

EasyRef Model Card

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Project Page | Paper | Code | 🤗 Demo

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Introduction

EasyRef is capable of modeling the consistent visual elements of various group image references with a single generalist multimodal LLM in a zero-shot setting.

<div align="center"> <img src='examples/framework.png'> </div>

Demos

More visualization examples are available in our project page.

Style, Identity, and Character Preservation

<img src='examples/teaser.png'>

Comparison with IP-Adapter

<img src='examples/qualitative.png'>

Compatibility with ControlNet

<img src='examples/controlnet.png'>

Inference

We provide the inference code of EasyRef with SDXL in easyref_demo.

Usage Tips

• EasyRef performs best when provided with multiple reference images (more than 2).
• To ensure better identity preservation, we strongly recommend that users upload multiple square face images, ensuring the face occupies the majority of each image.
• Using multimodal prompts (both reference images and non-empty text prompt) can achieve better results.
• We set scale=1.0 by default. Lowering the scale value leads to more diverse but less consistent generation results.

Cite

If you find EasyRef useful for your research and applications, please cite us using this BibTeX:

@article{easyref,
  title={EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM},
  author={Zong, Zhuofan and Jiang, Dongzhi and Ma, Bingqi and Song, Guanglu and Shao, Hao and Shen, Dazhong and Liu, Yu and Li, Hongsheng},
  journal={arXiv preprint arXiv:2412.09618},  
  year={2024}
}