AI-kasvojenparannin

Faces in photos go from pixelated to sharp in one click. Our face enhancer uses a model class similar to GFPGAN — specifically trained to restore facial detail in low-resolution shots, group photos where faces are small, or old photos where face detail has degraded. Drop the image, click Enhance, get back a version where eyes, lips, and eyebrows have actual definition.

How face enhancement is different from general upscaling

Generic AI upscalers (like our AI Upscaler) are trained across all kinds of images. They do well on clear subjects and recognisable textures, but tiny faces — say, 30×40 pixels in a group shot — confuse them. The model doesn't have enough information to know it's looking at a face, and ends up producing smeared or hallucinated features.

The face enhancer uses a model that's been pre-trained specifically on faces. Even from very-low-res input, it knows the rough geometry: two eyes, a nose, a mouth, eyebrows, hairline. It uses that prior knowledge to reconstruct plausible high-res detail. Result: a portrait that looks identifiable rather than abstract.

When to use the face enhancer

• Group shots where individual faces are small in the frame
• Wedding / event photos taken with phone cameras at distance
• Crowds where you want one face zoomed and clarified
• Old digital photos from 2006-era 5 MP cameras where face detail has aged badly
• Scanned old prints where faces have degraded due to print fade
• Webcam / video stills grabbed at sub-HD resolution

How to use it

1. Drop your photo. JPG, PNG, WebP, HEIC. Up to 10 MP on the free tier.
2. Optionally upscale at the same time. The tool can upscale 2× while enhancing faces — the combined pass takes about 12 seconds.
3. Wait for processing — 8–15 seconds depending on input size and number of faces detected.
4. Download the result. Output is a JPG. Faces in the image have visibly more definition; the rest of the photo is left untouched.

What to expect — and what not to

Realistic expectations: the AI doesn't recover lost identity. If a face was a 20×20 pixel blob in the original, the enhanced version will have a face — but it might be a different-looking face than the actual person. The model produces a plausible high-res face from the low-res input, not a forensic reconstruction.

For larger faces (≥150 pixels) the enhancement is essentially perfect — eyes get cleaner, skin texture comes back, hair strands appear. The result is identifiably the same person, just sharper.

For tiny faces (≤50 pixels) the result is "a person who could be them" rather than "definitely them". Useful for general aesthetic, less useful if you need to verify identity from the upscaled version.

For old photos with physical damage (scratches, fading, fold marks) on top of the face-detail issue, our Old Photo Restorer combines face enhancement with damage repair. For photos that need general colour/exposure cleanup in addition to face work, run the Photo Enhancer first then the face enhancer as a second pass.