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zhangqianhui/AdversarialNetsPapers resource

Awesome paper list with code about generative adversarial nets observed · 2026-08-28

github.com/zhangqianhui/AdversarialNetsPapers observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3630
  • days_rel: n/a
  • days_push: 1402
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

6570 stars · 1890 forks observed · 2026-08-28

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

A curated awesome-list of research papers on generative adversarial networks (GANs), organized by application area, theory, and tutorials, with links to code implementations. It is a reference resource rather than runnable software.

Use cases

  • find GAN papers with code
  • learn about generative adversarial networks
  • research image-to-image translation methods
  • survey GAN applications like super-resolution and inpainting
  • find tutorials and blogs on GANs
  • keep up with adversarial network research

When to choose

  • you need a curated reading list of GAN research with code links
  • you are surveying GAN applications across vision tasks
  • you want the original GAN paper plus follow-up work organized by topic

When to avoid

  • you need runnable software or a library to train GANs
  • you need up-to-date coverage of diffusion models and recent generative AI
  • you need a maintained project with a license and active releases

Facets

learning-resource · maturity maintenance

deep-learning machine-learning image-processing deep-learning computer-vision artificial-intelligence awesome-lists cross-platform gan awesome-list papers generative-models research

1 source

Member repositories

RepositoryRoleHealth v2
zhangqianhui/AdversarialNetsPapersmain32

For agents

markdown · JSON · MCP: product_card(name="zhangqianhui/AdversarialNetsPapers")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem