rotemtzaban/STIT

Health v2 · maintenance only

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1197 stars · 164 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

STIT (Stitch it in Time) is a research implementation of a GAN-based framework for semantic editing of faces in real videos, based on the paper 'Stitch it in Time: GAN-Based Facial Editing of Real Videos'. It leverages StyleGAN latent space alignment to produce temporally consistent facial manipulations in talking-head videos.

Use cases

• edit faces in real videos with GANs
• apply semantic facial manipulations to talking head videos
• invert real video frames into StyleGAN latent space
• achieve temporally consistent video face editing
• reproduce the Stitch it in Time research paper
• run StyleCLIP-based edits on video frames

When to choose

• you need temporally coherent facial editing of real videos
• you want a research-grade implementation of the STIT paper
• you work with StyleGAN inversion and video pipelines in PyTorch

When to avoid

• you need a polished end-user video editing application
• you lack a CUDA GPU or don't want to manage pretrained model downloads
• you need actively maintained software with recent updates

Facets

library · maturity maintenance

machine-learning deep-learning image-processing video-processing computer-vision deep-learning image-processing python gan stylegan face-editing video-editing research-code temporal-consistency stylegan-inversion paper-implementation video gpu linux

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