--- license: mit language: - en pipeline_tag: image-to-image tags: - face restoration - diffusion --- # Visual Style Prompt Learning Using Diffusion Models for Blind Face Restoration Visual Style Prompt (VSPBFR) Official PyTorch implementation of VSPBFR. [[paper]](https://www.sciencedirect.com/science/article/pii/S003132032401063X?via%3Dihub)
Blind face restoration aims to recover high-quality facial images from various unidentified sources of degradation, posing significant challenges due to the minimal information retrievable from the degraded images. Prior knowledge-based methods, leveraging geometric priors and facial features, have led to advancements in face restoration but often fall short of capturing fine details. To address this, we introduce a visual style prompt learning framework that utilizes diffusion probabilistic models to explicitly generate visual prompts within the latent space of pre-trained generative models. These prompts are designed to guide the restoration process. To fully utilize the visual prompts and enhance the extraction of informative and rich patterns, we introduce a style-modulated aggregation transformation layer. Extensive experiments and applications demonstrate the superiority of our method in achieving high-quality blind face restoration.
![Performance](./imgs/teaser3.png) ![Performance](./imgs/teaser4.png) --- license: mit ---