zhangqianhui/AdversarialNetsPapers resource
Awesome paper list with code about generative adversarial nets 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
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
- readme: https://github.com/zhangqianhui/AdversarialNetsPapers · fetched 2026-08-28 · a8034880fef7
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| zhangqianhui/AdversarialNetsPapers | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="zhangqianhui/AdversarialNetsPapers")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem