# wangzheallen/awesome-human-pose-estimation

Human Pose Estimation Related Publication

Repository: https://github.com/wangzheallen/awesome-human-pose-estimation
Canonical: https://ross.abutalabs.com/products/wangzheallen-awesome-human-pose-estimation
License Family: other
Topics: 3d-human-pose, 2d-human-pose, human-pose-estimation, video-pose-estimation, paper-reading, pose-generation, human-generation, real-time-pose-estimation, domain-knowdge, pose-focasting, pose-and-language, 3d-human-mesh, pose-dataset, motion-capture, motion-prediction, motion-planning, human-env-interaction, human-scene-interaction
Last push: 2020-08-07T18:44:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2868, "days_push": 2217, "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 1375, forks 209 (observed 2026-08-28T04:04:33.161490+00:00)

## What it is
A curated awesome-list of papers, datasets, benchmarks, and implementations for human pose estimation and related topics such as 3D human mesh, video pose, and motion prediction. It is a fork of cbsudux's list, customized for study and sharing.

## Use cases
- find papers on 2d and 3d human pose estimation
- discover datasets for pose estimation research
- find popular pytorch and tensorflow pose estimation implementations
- learn about human mesh recovery and motion capture research
- survey real-time pose estimation methods
- find benchmarks for human pose estimation

## When to choose
- you are starting research or study in human pose estimation
- you need a survey of papers, datasets, and code across pose-related subfields
- you want links to benchmarks and workshops in one place

## When to avoid
- you need a working pose estimation library or model to run
- you need actively maintained code rather than a paper list
- you need hand or face pose resources specifically (see related lists)

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: computer-vision, machine-learning
- domain: computer-vision, machine-learning, artificial-intelligence
- platform: cross-platform
- tags: awesome-list, human-pose-estimation, pose-estimation, motion-capture, 3d-human-mesh, paper-collection, datasets, benchmarks

## Member repositories
- wangzheallen/awesome-human-pose-estimation (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:33.161490+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 2026-08-30T04:40:35.739961+00:00, confidence not recorded.
  - readme: https://github.com/wangzheallen/awesome-human-pose-estimation (fetched 2026-08-28T04:04:33.161490+00:00, sha b4a8de17116f)
- Data as of 2026-08-30T08:39:29.467469+00:00.