#15 · Primary category: Computer Vision
GFPGAN
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
Project last updated:07/26/24
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Why we included this project
GFPGAN restores faces in photos that have been degraded by age, compression, or low resolution. It does blind face restoration, so it can repair a face without being told exactly what damaged it, relying on priors learned by a pretrained face GAN like StyleGAN2. The pipeline detects faces, restores them, and can optionally upscale the rest of the image with Real-ESRGAN, so you get a coherent full-image result rather than a patched face. It installs via pip, comes with a straightforward inference script and several downloadable model versions, and the authors host demos on Hugging Face and Replicate if you want to try it before integrating. That makes it a practical starting point for photo-restoration services, archival digitization, or any project that needs to salvage low-quality face imagery.
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