alex-damian/pulse

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

8023 stars · 1476 forks observed · 2026-08-28

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

PULSE is a Python research implementation of a CVPR 2020 paper that upscales low-resolution face photos by searching the latent space of a pretrained StyleGAN for high-resolution outputs that downscale to match the input. It produces realistic but imaginary faces, not reconstructions of the original person.

Use cases

• upscale low-resolution face photos to high resolution
• generate realistic high-res faces from blurry images
• explore StyleGAN latent space for image super-resolution
• reproduce CVPR 2020 super-resolution paper results
• research on GAN-based image upsampling

When to choose

• you need GAN-based face super-resolution for research or experimentation
• you have a CUDA GPU and want to explore StyleGAN latent space optimization
• you want perceptually realistic upscaled faces rather than pixel-accurate reconstruction

When to avoid

• you need to identify or reconstruct the actual original person from a blurred image
• you need a production-ready, licensed, actively maintained tool
• you have no CUDA-capable GPU
• you need super-resolution for non-face imagery

Facets

library · maturity maintenance

image-processing machine-learning deep-learning computer-vision image-processing deep-learning artificial-intelligence python windows super-resolution stylegan face-upsampling generative-models cvpr-2020 research-code linux gpu

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