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license: mit |
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language: |
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- en |
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pipeline_tag: image-to-image |
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tags: |
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- face restoration |
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- diffusion |
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# Visual Style Prompt Learning Using Diffusion Models for Blind Face Restoration Visual Style Prompt (VSPBFR) |
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Official PyTorch implementation of VSPBFR. |
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[[paper]](https://www.sciencedirect.com/science/article/pii/S003132032401063X?via%3Dihub) |
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<div style="text-align: justify"> 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. |
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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. |
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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.</div> |
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license: mit |
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