Genuine Neural Restoration
A generative facial prior reconstructs lost detail instead of only sharpening pixels.
3-step process
How GFPGAN Works
From a degraded, blurry input to a crystal-clear, high-fidelity portrait — every stage is transparent, measurable, and takes less than one second.
- Upload
Detect and align faces
The pipeline detects landmarks and normalizes pose so restoration starts from stable geometry.
- Process
Apply generative facial prior
GFPGAN rebuilds detail while preserving expression, identity, and structure.
- Download
Blend and upscale output
The restored face is blended back into the frame and prepared for final delivery.
Why GFP-GAN Leads
Built for Perfection
Restore every detail in old, blurry, or damaged photos with GFPGAN AI. Experience lifelike face enhancement and flawless photo restoration in seconds.
100% Private - Zero Upload
Your images are processed in the browser and never leave your device.
4 Model Variants
Choose GFP-GAN v1.2 through v1.5 for different quality and speed targets.
Ultra-HD Output
Prepare restored faces for portraits, archives, print, and sharing.
Identity Retention
Restore clarity while keeping the original person recognizable.
Production-Grade Speed
Fast browser previews make restoration practical for everyday use.
Open-source on GitHub MIT licensed 10M+ downloads Cited in 400+ papers No account required
Results That Speak for Themselves
From family archivists to studio post-production, professionals use GFP-GAN to restore faces faster.
"The before and after difference is extraordinary."
"GFPGAN fit into our workflow quickly."
"It understands what a natural face should look like."
"Archive frames became clear enough for our workflow."
"Privacy-first browser processing matters."
"I finally saw the expression clearly again."
4.9
Average rating across 12,400+ verified reviews on GitHub, Product Hunt and Hugging Face
Model Quality Matrix
GFP-GAN Model and Runtime Matrix
| Variant | Target Resolution | Identity Fidelity | Runtime |
|---|---|---|---|
| gfpgan 1.2 | 512px | High | Fast |
| gfpgan 1.3 | 512px | High+ | Fast |
| gfpgan 1.4 | 1024px | Very High | Balanced |
| gfpgan 1.5 | 1024px | Ultra | Balanced |
Speed Profile
Processing Speed
Higher = faster (relative scale)
- gfpgan 1.2 Fast · 512px
- gfpgan 1.3 Fast · 512px
- gfpgan 1.4 Balanced · 1024px
- gfpgan 1.5 Balanced · 1024px
Identity Fidelity
gfpgan 1.2 High
gfpgan 1.3 High+
gfpgan 1.4 Very High
gfpgan 1.5 Ultra
GFP-GAN Pipeline Explorer
Step through each stage of the restoration pipeline. Watch how detail recovery and identity confidence evolve from raw degraded input to premium output.
Pipeline Stages
Input & Face Detection
Locate facial regions, align landmarks, and normalise crop geometry to 512×512.
- Detail Recovery 62%
- Identity Retention 88%
- Processing Speed 95%
Before / After Lens
Degraded Restored
FAQ
Frequently Asked Questions About GFPGAN
Everything you need to know about GFP-GAN — from model selection to integrating with production pipelines.
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01 What is GFPGAN?
GFPGAN is an AI face restoration model that rebuilds realistic detail in degraded portraits.
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02 What photos can it restore?
It works best on portraits, old family photos, compressed images, blurry selfies, and frames with visible faces.
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03 Are my images uploaded?
No. The browser tool processes images locally on your device.