# jinwchoi/awesome-action-recognition

A curated list of action recognition and related area resources

Repository: https://github.com/jinwchoi/awesome-action-recognition
Canonical: https://ross.abutalabs.com/products/awesome-action-recognition
License Family: other
Topics: awesome-list, awesome, action-recognition, action-classification, action-detection, activity-recognition, activity-understanding, video-understanding, video-recognition, video-processing, object-recognition, pose-estimation
Last push: 2023-05-13T17:00:12+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3632, "days_push": 1208, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4016, forks 716 (observed 2026-08-28T04:08:32.430410+00:00)

## What it is
A curated awesome-list of resources for video action recognition and related areas such as object recognition and pose estimation. It collects research papers, survey posts, competitions, and code links for video understanding.

## Use cases
- find papers on human action recognition in video
- learn about deep learning for video classification
- discover pose estimation research resources
- survey video understanding methods before starting a project
- find datasets and competitions for action recognition
- keep up with state-of-the-art video recognition models

## When to choose
- you need a starting point for researching action recognition or video understanding
- you want curated links to landmark papers and code implementations
- you are surveying related areas like object recognition or pose estimation

## When to avoid
- you need a working action recognition library or model rather than a reading list
- you need actively maintained tooling or guaranteed up-to-date content
- you need production video processing software

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, computer-vision, video-processing
- domain: computer-vision, machine-learning, deep-learning, awesome-lists
- platform: cross-platform
- tags: awesome-list, action-recognition, video-understanding, pose-estimation, curated-resources, research-papers, video

## Member repositories
- jinwchoi/awesome-action-recognition (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:32.430410+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:23:58.439007+00:00, confidence not recorded.
  - readme: https://github.com/jinwchoi/awesome-action-recognition (fetched 2026-08-28T04:08:32.430410+00:00, sha bf24b75b8ad9)
- Data as of 2026-08-30T08:39:29.467469+00:00.