pprp/awesome-attention-mechanism-in-cv resource
Awesome List of Attention Modules and Plug&Play Modules in Computer Vision observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
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: 2061
- days_rel: n/a
- days_push: 1210
- n_releases_24m: 0
Adoption not part of the score
1282 stars · 172 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A curated awesome list of attention mechanisms and plug-and-play modules for computer vision, with links to papers and implementations. It covers SENet, CBAM, Non-Local Networks, and Vision Transformers.
Use cases
- find attention modules for computer vision models
- learn about vision transformer papers
- find plug-and-play attention blocks for pytorch
- compare channel and spatial attention mechanisms
- find implementations of SENet or CBAM
When to choose
- researching attention mechanisms for image models
- looking for ready-to-use attention module implementations
When to avoid
- you need production-ready maintained code
- you want a runnable library rather than a link collection
Facets
learning-resource · maturity maintenance
machine-learning computer-vision deep-learning computer-vision deep-learning awesome-lists python
1 source
- readme: https://github.com/pprp/awesome-attention-mechanism-in-cv · fetched 2026-08-28 · 4e0cd833a2ba
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| pprp/awesome-attention-mechanism-in-cv | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="pprp/awesome-attention-mechanism-in-cv")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem