Who should use the Restore faces workflow?
Teams or solo builders working on creativity tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Creativity
Practical execution plan for restore faces with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
A high-resolution, sharp final image ready for printing or sharing
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
A high-resolution, sharp final image ready for printing or sharing
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use Lensa AI Photo Editor to a clean, high-quality source image ready for restoration processing. Then, you pass the output to Topaz Gigapixel AI to a 2x-4x upscaled image with reduced noise and sharper facial features. Then, you pass the output to GFPGAN to a face with reconstructed features, smooth skin, and corrected asymmetry, while retaining original identity. Then, you pass the output to Lensa AI Photo Editor to a natural-looking face with realistic skin texture and consistent color matching the original photo. Finally, Imglarger is used to a high-resolution, sharp final image ready for printing or sharing.
Assess and prepare the source image
A clean, high-quality source image ready for restoration processing
Upscale and enhance initial resolution
A 2x-4x upscaled image with reduced noise and sharper facial features
Restore facial details with AI face restoration
A face with reconstructed features, smooth skin, and corrected asymmetry, while retaining original identity
Refine skin texture and color consistency
A natural-looking face with realistic skin texture and consistent color matching the original photo
Final upscale and export for delivery
A high-resolution, sharp final image ready for printing or sharing
Start by examining the photo for damage type (scratches, blur, missing parts) and resolution. Scan or upload at highest possible quality. Crop to focus on the face area to reduce processing artifacts.
Why Lensa AI Photo Editor: Lensa AI Photo Editor provides photo retouching and object removal, which are suitable for basic image preparation and cleanup before restoration.
Use an AI upscaler to increase image resolution by 2x-4x, which gives the face restoration model more pixels to work with. This step reduces noise and sharpens edges before detailed restoration.
Why Topaz Gigapixel AI: Topaz Gigapixel AI is specifically designed for image upscaling and detail enhancement, directly matching the step's requirement.
Apply a dedicated face restoration model (e.g., GFPGAN, CodeFormer, or Remini) to reconstruct missing or damaged facial features. The AI will fill in eyes, mouth, skin texture, and symmetrize the face based on learned patterns.
Why GFPGAN: GFPGAN is a specialized blind face restoration tool, directly matching the step's requirement for AI face restoration.
After AI restoration, skin may appear plastic or overly smooth. Use a photo editor to add subtle texture, adjust color balance, and blend restored areas with the original photo's lighting and tone.
Why Lensa AI Photo Editor: Lensa AI Photo Editor provides photo retouching capabilities that can refine skin texture and color consistency.
Perform a final upscale to the target output resolution (e.g., 4K for print, 1080p for digital). Sharpen slightly and export in a lossless format (PNG or TIFF) to preserve quality.
Why Imglarger: Imglarger provides AI image upscaling and photo enhancement, suitable for final upscaling and sharpening before export.
§ Before you start
Teams or solo builders working on creativity tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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