cjwbw / prompt-free-diffusion

Prompt-free Diffusion

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Prompt-Free Diffusion

Introduction

Prompt-Free Diffusion is a diffusion model that relys on only visual inputs to generate new images, handled by Semantic Context Encoder (SeeCoder) by substituting the commonly used CLIP-based text encoder. SeeCoder is reusable to most public T2I models as well as adaptive layers like ControlNet, LoRA, T2I-Adapter, etc. Just drop in and play!

Performance

Network

Citation

@article{xu2023prompt,
  title={Prompt-Free Diffusion: Taking" Text" out of Text-to-Image Diffusion Models},
  author={Xu, Xingqian and Guo, Jiayi and Wang, Zhangyang and Huang, Gao and Essa, Irfan and Shi, Humphrey},
  journal={arXiv preprint arXiv:2305.16223},
  year={2023}
}

Acknowledgement

Part of the codes reorganizes/reimplements code from the following repositories: Versatile Diffusion official Github and ControlNet sdwebui Github, which are also great influenced by LDM official Github and DDPM official Github