sczhou/CodeFormer

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

18117 stars · 3719 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

CodeFormer is a PyTorch-based blind face restoration model using a codebook lookup transformer, published at NeurIPS 2022. It restores and enhances degraded face images with support for super-resolution, inpainting, colorization, and video input.

Use cases

• restore old blurry face photos
• enhance low-quality faces in images
• upscale and denoise faces in videos
• fix degraded AI-generated face art
• colorize black-and-white face images
• inpaint missing regions of aligned face crops

When to choose

• you need state-of-the-art blind face restoration on degraded photos
• you want pretrained checkpoints plus inference and training code
• you need face enhancement for images or videos in a Python pipeline

When to avoid

• you need general-purpose image restoration beyond faces
• you lack a GPU or want lightweight real-time processing
• you require a permissive open-source license for commercial use

Facets

library · maturity stable

image-processing machine-learning deep-learning computer-vision image-processing deep-learning artificial-intelligence python cross-platform face-restoration super-resolution blind-face-restoration vqgan transformer codebook face-inpainting colorization pytorch neurips-2022 gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="sczhou/CodeFormer")