GFPGAN — AI Face Restoration & Enhancement Model 🖼️🔢❓ → 🖼️

▶️ 115.0M runs 📅 Sep 2021 ⚙️ Cog 0.4.2 🔗 GitHub 📄 Paper ⚖️ License

face-detection face-restoration image-restoration image-upscaling face-enhancement portrait

GFPGAN (Generative Facial Prior GAN) is one of the most widely used face restoration models. Developed by TencentARC, it uses pretrained face generation knowledge to fill in missing facial details that simpler upscaling methods cannot recover.

About

GFPGAN by TencentARC is a practical face restoration model that enhances and restores degraded face images. It leverages generative facial priors from a pretrained face GAN (StyleGAN2) to recover realistic facial details — eyes, mouth, hair — from low-quality, blurry, or compressed face photos.

Key capabilities

Face restoration — recover detail from blurry, noisy, or low-resolution face images
Face enhancement — improve clarity and sharpness of portrait photos
Old photo repair — restore faces in vintage or damaged photographs
Video frame enhancement — improve face quality in individual video frames

GFPGAN balances fidelity (staying close to the input) with quality (generating realistic details), making it suitable for both creative and restoration workflows.

Example Output

Output

Performance Metrics

1.67s Prediction Time

1.97s Total Time

All Input Parameters

{
  "img": "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
  "scale": 2,
  "version": "v1.4"
}

Input Parameters

img (required) Type: string: Input
scale Type: numberDefault: 2: Rescaling factor
version Default: v1.4: GFPGAN version. v1.3: better quality. v1.4: more details and better identity.

Output Schema

Output

Type: string • Format: uri

Example Execution Logs

/tmp/tmpky22vsq_187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg v1.4 2.0

Version Details

Version ID: 0fbacf7afc6c144e5be9767cff80f25aff23e52b0708f17e20f9879b2f21516c
Version Created: March 14, 2024

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