A face-restoration model (GFPGAN, CodeFormer) recovers degraded facial detail in the generated or photographed image, while a separate general-purpose upscaler (Real-ESRGAN) handles background and non-face regions.
Properties
family
restore-upscale
modality
image -> image
whyMultiModel
Face restoration and general upscaling are fundamentally different tasks requiring specialized models: face models exploit facial priors (identity, geometry) that general upscalers lack, and general upscalers handle textures and backgrounds that face models cannot attend to. Base-refiner pipelines add a detail-finishing pass on the whole image; this pattern uses region-split specialist models where each model operates on a distinct pixel domain.
steps
[object Object], [object Object]
controls
CodeFormer fidelity weight (0=quality, 1=identity fidelity); Real-ESRGAN model variant (x4plus, x4plus-anime); face detection confidence threshold; blend mask feathering.
exampleStack
GFPGAN v1.4 (face regions) + Real-ESRGAN x4plus (background); or CodeFormer + Real-ESRGAN via A1111 Extra tab or ComfyUI FaceRestoreCF node.
useCases
[Restoring small or degraded faces in generated images][Old photo revival (scan to high-res)][Upscaling AI portraits without over-smoothing faces]
pitfalls
Face detection failures on unusual angles or heavy occlusion leave faces unrestored; high CodeFormer fidelity may preserve blur from the original; seam artifacts at the face/background boundary if blend mask is not feathered.
