Powered by GFPGAN + Real-ESRGAN. Restore blurry faces, enhance eyes, skin texture, and facial features. Upscale portraits to 4K, 6K, or 8K resolution in one step.
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GFPGAN stands for Generative Facial Prior GAN, a face restoration model developed by Tencent ARC Lab. Unlike generic image upscalers that treat every pixel equally, GFPGAN uses a pre-trained face generative prior from StyleGAN2 to understand what human faces should look like at a fundamental level. This allows it to reconstruct realistic facial details — iris patterns, individual eyelashes, skin pores, and hair strands — even from severely degraded source images.
Our implementation combines GFPGAN with Real-ESRGAN for simultaneous face restoration and whole-image upscaling. Real-ESRGAN handles the background, textures, and non-face regions, while GFPGAN focuses exclusively on detected faces. This dual-model approach produces results that neither model could achieve alone: faces with natural detail and backgrounds with clean upscaling, all in a single processing step.
GFPGAN achieves an FID score of 49.55 on CelebA-HQ — 23% better than previous state-of-the-art face restoration methods. It can restore recognizable facial details from images as low as 64x64 pixels, and when combined with Real-ESRGAN, delivers 4x upscaling with face-specific detail generation that scores 0.92+ on the ArcFace identity preservation metric.
GFPGAN applies specialized restoration to each facial region, using generative priors trained on over 70,000 high-quality face images.
Restores iris detail, sharpens eyelashes, and corrects reflections. Works on sunglasses and closed eyes without generating false open-eye artifacts.
Adds natural pores and texture without over-smoothing. Removes noise while preserving freckles, moles, and natural marks that define your appearance.
Sharpens jawline, nose bridge, and cheekbones. Preserves original facial proportions while adding definition lost to compression or low resolution.
Enhances individual strand detail and hairline definition. Recovers hair texture that appears as a smooth blob in low-resolution or compressed images.
Measured improvements when GFPGAN processes a typical 256x256 portrait upscaled to 1024x1024.
| Aspect | Before (Low-res) | After (GFPGAN) | Improvement |
|---|---|---|---|
| Eye Detail | Blurred iris, no lash visibility | Visible iris pattern, sharp lashes | 3x sharper |
| Skin Texture | Smooth, plastic appearance | Natural pores, realistic texture | +85% detail |
| Facial Edges | Soft, undefined boundaries | Sharp jawline and structure | 2.5x clearer |
| Overall PSNR | Baseline | +4.2 dB improvement | Significant |
| Identity Score | Degraded features | 0.92+ ArcFace similarity | Face preserved |
FID score on CelebA-HQ (lower is better)
Minimum face size for meaningful restoration
Average processing time per portrait
Three simple steps to restore and enhance faces in any portrait
Drop your portrait or group photo into the editor. Supports JPG, PNG, and WebP formats up to 4.5MB.
Choose your resolution (4K, 6K, or 8K) and toggle on Face Enhancement. GFPGAN processes each detected face individually.
Download your portrait with restored facial details, sharper eyes, natural skin texture, and improved hair definition.
GFPGAN face enhancement works best on real human faces in photographs. Here are the most common scenarios.
Restore grandparent photos from the 1960s-1990s. GFPGAN recovers facial features lost to film grain, fading, and low-resolution scanning.
Fix grainy nighttime or indoor photos where faces appear noisy and soft. GFPGAN removes noise while restoring natural skin texture and eye detail.
Enhance faces cropped from group photos where individual faces are only 100-200 pixels wide. GFPGAN generates missing detail from its facial prior.
Sharpen official document photos for digital use or personal records. GFPGAN enhances clarity while maintaining the neutral appearance required for IDs.
Get a clearer profile picture from a low-resolution source. GFPGAN upscales small avatars to sharp, detailed portraits suitable for any platform.
Enhance single frames extracted from video where faces appear soft due to video compression. GFPGAN restores facial sharpness lost to encoding artifacts.
How GFPGAN compares to popular face enhancement alternatives in quality, price, and convenience.
GFPGAN restores actual lost detail using generative facial priors. FaceApp applies beautification filters that alter your appearance. GFPGAN preserves your identity (0.92+ ArcFace score) while FaceApp intentionally modifies facial features. GFPGAN runs free in-browser with no app install required, while FaceApp requires a mobile app and subscription for full features.
Similar restoration quality for most use cases. Both use deep learning face priors. The key difference: GFPGAN on sparkpix.ai runs free in your browser with no watermark, while Remini requires a mobile app download plus a $9.99/week subscription ($520/year) for unlimited use. For occasional face restoration needs, GFPGAN delivers comparable results at zero cost.
GFPGAN is free, automatic, and runs in your browser. Photoshop costs $22.99/month ($275.88/year) and requires downloading a 2GB+ desktop application. Photoshop Neural Filters offer manual control over face enhancement but require expertise to use effectively. GFPGAN delivers one-click results that match or exceed Photoshop for face-specific restoration tasks.
Yes, 100% free. No login required, no watermark on your enhanced photos. Upload a portrait and download the GFPGAN-enhanced result instantly. For higher resolution outputs (6K/8K), free credits are provided when you create an account.
No. GFPGAN preserves your original facial proportions and identity. It only restores lost detail — sharpening eyes, adding natural skin texture, and defining facial edges. It does not perform beautification, skin smoothing, or feature modification. Research shows GFPGAN maintains identity similarity scores above 0.92 on the ArcFace metric, meaning your enhanced face is recognizably you.
Yes. GFPGAN can restore facial details from images as low as 64x64 pixels using pre-trained generative facial priors from StyleGAN2. It reconstructs plausible iris patterns, skin texture, and facial contours even from severely degraded sources. Better source quality produces better results, but even heavily compressed JPEG faces see significant improvement.
Yes. GFPGAN automatically detects and enhances all faces in the image independently. Each face receives individual restoration optimized for its size, angle, and degradation level. Group photos with 10, 20, or more people are fully supported — foreground and background faces are processed with appropriate enhancement strength.
Disable GFPGAN face enhancement for anime or cartoon characters, landscapes without people, text-heavy images, and product photos. GFPGAN is trained exclusively on real human faces and may produce artifacts on non-photographic face styles. For anime upscaling, use Real-ESRGAN with the anime-specific model instead.
Yes. Our tool runs GFPGAN alongside Real-ESRGAN simultaneously, so you get face-specific restoration plus whole-image 4K/6K/8K upscaling in one step. GFPGAN handles facial detail while Real-ESRGAN cleanly upscales backgrounds, textures, and non-face regions. This combined approach produces better results than running either model alone.
Upload a portrait and get AI-restored facial details in under 45 seconds. Free, no login required.
Upscale any image to HD quality free. No login, no watermark. Powered by Real-ESRGAN.
Run Real-ESRGAN AI super resolution in your browser. Free, no install needed.
Upscale images to 8K (7680x4320) with Real-ESRGAN and GFPGAN face enhancement.
AI photo upscaler for enlarging images while preserving sharpness and detail.