taoxugit/AttnGAN

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1363 stars · 425 forks observed · 2026-08-28

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

A PyTorch implementation of AttnGAN, a fine-grained text-to-image generative adversarial network with multi-stage attention mechanisms from a CVPR 2018 paper. It includes training scripts, pretrained models for the CUB birds and COCO datasets, and sampling code to generate images from text captions.

Use cases

• generate images from text descriptions
• reproduce AttnGAN paper results
• train a text-to-image GAN on birds or COCO dataset
• experiment with attentional GAN architectures
• generate bird images from custom captions
• research fine-grained text-to-image synthesis

When to choose

• you need to reproduce or build on the AttnGAN CVPR 2018 paper
• you want pretrained text-to-image GAN models for birds or COCO
• you are studying attention mechanisms in GANs for research

When to avoid

• you need modern high-quality text-to-image generation (use diffusion models instead)
• you need a production-ready or maintained product
• you cannot use Python 2.7-era dependencies or older PyTorch versions

Facets

library · maturity maintenance

machine-learning deep-learning image-processing machine-learning deep-learning computer-vision python text-to-image gan pytorch attention research-code cvpr-2018 natural-language-processing linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="taoxugit/AttnGAN")