01
Repair physical damage
Target scratches, dust, tears, creases, stains, and missing patches as named defects.
FireRed professional photo restoration
Restore Old Photos with AI
Repair scratches, fading, stains, and lost detail with a natural-language restoration workflow. FireRed Image Edit is designed to enhance damaged photos without turning every face into a synthetic portrait.
Scratch and stain repair Identity-aware restoration Natural detail recovery
Restoration with explicit constraints
Recover detail without erasing the photograph's history
A good restoration removes damage while preserving the people, lighting, grain, and era that make the source meaningful.
02
Preserve identity
Tell the model to keep faces, expressions, pose, age, clothing, and family resemblance unchanged.
03
Control the finish
Choose faithful black-and-white restoration, subtle color recovery, or careful colorization as separate goals.
FireRed restoration in the official showcase
The FireRedTeam showcase includes old-photo repair alongside general object, portrait, and compositional edits. The restoration pair appears at the lower right.
Damage removal
Surface wear and fading are reduced without replacing the entire photographic scene.
Face recovery
The result restores readable facial features while keeping the subjects recognizable.
Period-aware finish
Texture and wardrobe remain grounded in the original image instead of looking like a modern studio remake.
How to restore an old photo with AI
Separate repair, enhancement, and optional colorization into clear steps so each result can be evaluated.
1
Scan or photograph carefully
Use even lighting, avoid glare, and capture the highest practical resolution before asking AI to reconstruct detail.
2
List damage and invariants
Name scratches, fading, or missing areas, then state that identity, expression, pose, clothing, and framing must stay unchanged.
3
Compare at full resolution
Inspect eyes, teeth, hands, jewelry, text, and repeated patterns. Refine one defect at a time if the first pass invents detail.
Old photo restoration use cases
The workflow is useful for personal archives and publishing projects where the source must remain recognizable and credible.
Family archive recovery
Clean up portraits and group photos before printing, sharing, or adding them to a digital family history.
Historical publication
Prepare damaged source images for articles or exhibits while retaining provenance and documenting that restoration was applied.
Print-ready enhancement
Improve clarity and tonal balance for a new print without oversmoothing faces or removing authentic grain.
Prompt recipes for faithful restoration
Keep the request conservative. Repair the named damage and repeat the details that must not change.
Black-and-white repair
“Repair scratches, dust, creases, and faded contrast. Preserve every person's identity, expression, pose, clothing, film grain, and black-and-white character.”
Face-detail recovery
“Recover subtle facial detail from this damaged portrait without changing age, expression, hairstyle, face shape, or period lighting.”
Careful colorization
“First restore the damaged photo, then add restrained historically plausible color. Keep skin tones natural and preserve the original composition and grain.”
Restoration quality and authenticity checks
AI can reconstruct plausible details that were never present. Treat the result as an interpretation and keep the source file.
Compare identities
Check facial proportions, asymmetry, distinctive marks, and expressions against other known photos when available.
Watch invented detail
Inspect eyes, teeth, hands, jewelry, uniforms, signage, and background objects for confident but inaccurate reconstruction.
Keep restoration provenance
Archive the original, the prompt, and the restored derivative so later viewers can distinguish source from reconstruction.
Why use FireRed for photo restoration
Professional photo restoration is a stated FireRed capability, supported by an instruction-based workflow and identity-focused 1.1 improvements.
Natural-language control
Describe the exact damage and desired finish instead of relying on a single opaque enhancement slider.
Identity-focused model updates
FireRed Image Edit 1.1 specifically improves portrait consistency, useful when faces must remain recognizable.
Open-source evidence
Official model resources, examples, code, and a technical report make the underlying capability easier to inspect.
AI old photo restoration FAQ
Practical guidance for repairing damaged family and historical photographs with AI.
Can AI restore badly damaged old photos?
It can repair many scratches, stains, creases, and faded regions, but severely missing areas require reconstruction and may not be historically exact.
Will the restored face still look like the same person?
Ask explicitly to preserve identity, age, expression, and face shape. Compare the result against the source and other reference photos.
Can FireRed colorize black-and-white photos?
You can request colorization, but treat colors as an interpretation unless you have reliable references for clothing, skin, objects, and setting.
Should I restore and colorize in one prompt?
For difficult images, restore damage first and colorize in a separate pass. That makes each change easier to inspect and correct.
How do I scan an old photo for restoration?
Use a flat, evenly lit scan at the highest practical resolution. Avoid glare, perspective distortion, filters, and aggressive compression.
Can AI remove scratches and creases?
Yes. Name those defects directly and specify that facial features, clothing, text, and background structure must remain unchanged.
How do I avoid plastic-looking skin?
Ask to preserve natural skin texture and film grain, avoid beauty retouching, and reduce smoothing in a follow-up instruction.
Can I restore a group photograph?
Yes, but inspect each face separately. Group photos contain smaller features and increase the risk of identity drift.
What details are most likely to be invented?
Tiny facial features, jewelry, hands, text, uniforms, repeating patterns, and objects hidden by large damaged areas deserve extra scrutiny.
Should I keep the original photo file?
Always. Store an untouched master scan and export the AI restoration as a separate derivative with the prompt and date recorded.
Is FireRed Image Edit open source?
Yes. FireRedTeam publishes the model resources and code through official GitHub, Hugging Face, and ModelScope pages.
Where should I begin restoring a photo?
Start with repair and contrast recovery, keep the prompt conservative, then evaluate identity and authenticity before attempting colorization.
Repair the damage while preserving the memory
Describe the physical defects, state what must remain unchanged, and open the restoration prompt in FireRed Image Edit.
Keep the source
Archive an untouched high-resolution scan.
Restore conservatively
Repair named damage before adding color or stylistic changes.
Verify every face
Inspect identity and small details at full resolution.