ai-forever/ghost

Health v2 · maintenance only

Adoption not part of the score

1582 stars · 308 forks observed · 2026-08-28

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

GHOST (Generative High-fidelity One Shot Transfer) is a one-shot face swap pipeline for images and videos, published as an IEEE paper and implemented in PyTorch. It swaps a face from a single source image onto target images or videos using generative techniques.

Use cases

• swap a face from one photo onto another image
• put a face onto a video with a single reference photo
• experiment with one-shot deepfake generation models
• reproduce GAN-based face swap research from the GHOST paper
• try face swapping in Google Colab without local GPU

When to choose

• you need one-shot face swapping without training a model per identity
• you want a research-grade face swap implementation with a published paper
• you want to run face swap on both images and videos
• you want a Colab demo to test quickly

When to avoid

• you need production-grade, polished end-user face swap software
• you require real-time face swapping performance
• your use case involves swapping faces without consent or other unethical purposes, which the project explicitly forbids
• you need a maintained GUI application rather than a research codebase

Facets

library · maturity active

computer-vision image-processing video-processing deep-learning machine-learning computer-vision deep-learning image-processing python cross-platform face-swap deepfake one-shot gan pytorch research video gpu

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