# A Review on Human Pose Estimation

arXiv: https://arxiv.org/abs/2110.06877 · HTML: https://mlsanity.com/paper/2110.06877/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 55 references that are in the map.
- First posted on arXiv 13 Oct 2021.

## Builds on (most cited first, 27 of 27)

- [Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1611.08050/) (2016)
- [How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)](https://mlsanity.com/paper/1703.07332/) (2017)
- [3D human pose estimation in video with temporal convolutions and semi-supervised training](https://mlsanity.com/paper/1811.11742/) (2018)
- [Convolutional Pose Machines](https://mlsanity.com/paper/1602.00134/) (2016)
- [Learning to Estimate 3D Hand Pose from Single RGB Images](https://mlsanity.com/paper/1705.01389/) (2017)
- [High-Resolution Representations for Labeling Pixels and Regions](https://mlsanity.com/paper/1904.04514/) (2019)
- [Whole-Body Human Pose Estimation in the Wild](https://mlsanity.com/paper/2007.11858/) (2020)
- [PoseTrack: A Benchmark for Human Pose Estimation and Tracking](https://mlsanity.com/paper/1710.10000/) (2017)
- [GANerated Hands for Real-time 3D Hand Tracking from Monocular RGB](https://mlsanity.com/paper/1712.01057/) (2017)
- [Look at Boundary: A Boundary-Aware Face Alignment Algorithm](https://mlsanity.com/paper/1805.10483/) (2018)
- [Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image](https://mlsanity.com/paper/1907.11346/) (2019)
- [Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking](https://mlsanity.com/paper/1904.01324/) (2019)
- [Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image](https://mlsanity.com/paper/1701.00295/) (2017)
- [Detect-and-Track: Efficient Pose Estimation in Videos](https://mlsanity.com/paper/1712.09184/) (2017)
- [BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis](https://mlsanity.com/paper/1704.02612/) (2017)
- [Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose](https://mlsanity.com/paper/1811.12004/) (2018)
- [MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation](https://mlsanity.com/paper/2007.07227/) (2020)
- [Efficient Online Multi-Person 2D Pose Tracking with Recurrent Spatio-Temporal Affinity Fields](https://mlsanity.com/paper/1811.11975/) (2018)
- [3D Human Pose Estimation with 2D Marginal Heatmaps](https://mlsanity.com/paper/1806.01484/) (2018)
- [Fast Facial Landmark Detection and Applications: A Survey](https://mlsanity.com/paper/2101.10808/) (2021)
- [Active Learning for Bayesian 3D Hand Pose Estimation](https://mlsanity.com/paper/2010.00694/) (2020)
- [Nonparametric Structure Regularization Machine for 2D Hand Pose Estimation](https://mlsanity.com/paper/2001.08869/) (2020)
- [Attention! A Lightweight 2D Hand Pose Estimation Approach](https://mlsanity.com/paper/2001.08047/) (2020)
- [Hand Pose Estimation: A Survey](https://mlsanity.com/paper/1903.01013/) (2019)
- [HandAugment: A Simple Data Augmentation Method for Depth-Based 3D Hand Pose Estimation](https://mlsanity.com/paper/2001.00702/) (2020)
- [Rule Of Thumb: Deep derotation for improved fingertip detection](https://mlsanity.com/paper/1507.05726/) (2015)
- [Multi-view consensus CNN for 3D facial landmark placement](https://mlsanity.com/paper/1910.06007/) (2019)

## Built on by (most cited first, 1 of 1)

- [Deep Learning Based Illegal Bowling Action Detection](https://mlsanity.com/paper/2610.07223/) (2026)

## Abstract (arXiv)

The phenomenon of Human Pose Estimation (HPE) is a problem that has been explored over the years, particularly in computer vision. But what exactly is it? To answer this, the concept of a pose must first be understood. Pose can be defined as the arrangement of human joints in a specific manner. Therefore, we can define the problem of Human Pose Estimation as the localization of human joints or predefined landmarks in images and videos. There are several types of pose estimation, including body, face, and hand, as well as many aspects to it. This paper will cover them, starting with the classical approaches to HPE to the Deep Learning based models.