megvii-research/NAFNet

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3148 stars · 400 forks observed · 2026-08-28

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

NAFNet is the official PyTorch implementation of a state-of-the-art image restoration network that removes nonlinear activation functions. It provides pretrained models for image deblurring, denoising, and stereo image super-resolution.

Use cases

• remove blur from photos
• denoise noisy images
• upscale stereo image pairs
• train a custom image restoration model
• benchmark restoration models on GoPro or SIDD
• restore low-quality images with a deep learning model

When to choose

• you need state-of-the-art deblurring or denoising quality
• you want a simple, efficient restoration baseline in PyTorch
• you work on stereo image super-resolution

When to avoid

• you need a general-purpose image editor rather than a research model
• you cannot run GPU inference
• you need a permissively licensed model (license is non-standard)

Facets

library · maturity stable

image-processing machine-learning deep-learning computer-vision image-processing deep-learning machine-learning python image-restoration deblurring denoising super-resolution pytorch eccv2022 low-level-vision gpu

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markdown · JSON · MCP: product_card(name="megvii-research/NAFNet")