Recover Faces
Intelligent facial Restoration for low-resolution images
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Intelligent facial Restoration for low-resolution images
Recover Faces is a specialized facial reconstruction model designed to restore recognizable facial detail from low-resolution, damaged, or heavily compressed images. When facial information is missing or unreadable, Recover Faces reconstructs plausible features rather than strictly preserving original pixels.
This model is typically combined with another enhancement. Face Recovery includes both Realistic and Creative variants, allowing users to balance fidelity and recovery strength based on source quality. Because these models are reconstructive by design, results may include subtle changes to expressions or smoothing of skin, hair, or fine facial details in order to produce a coherent, usable face.
Recover Faces is intended for portraits and people-focused imagery where standard upscaling cannot recover meaningful facial structure.
Reconstructs facial detail from extremely low-resolution or damaged images
Automatically detects and processes multiple faces within a single image
Enables usable portrait results where traditional upscaling fails
Output MP
Credits
Endpoint
model — "Faces"
Model-Specific Parameters
strength — decimal between 0 and 1, default 0.8
noise_sigma — decimal between 0.001 and 0.1, default 0.015
blur_sigma — decimal between 0.01 and 2.0, default 0.4
noise_seed — integer between 1 and 2000, default 1
reference_uri — string, optional
This model works best on smaller images, where the face in the input image is less than 512 x 512 pixels. For larger images, we recommend using Detail Faces.
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