# Advances in Human Action Recognition: A Survey

arXiv: https://arxiv.org/abs/1501.05964 · HTML: https://mlsanity.com/paper/1501.05964/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jan 2015.

## Built on by (most cited first, 3 of 3)

- [Levels of explainable artificial intelligence for human-aligned conversational explanations](https://mlsanity.com/paper/2107.03178/) (2021)
- [Video-based Human Action Recognition using Deep Learning: A Review](https://mlsanity.com/paper/2208.03775/) (2022)
- [A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction](https://mlsanity.com/paper/2110.13280/) (2021)

## Abstract (arXiv)

Human action recognition has been an important topic in computer vision due to its many applications such as video surveillance, human machine interaction and video retrieval. One core problem behind these applications is automatically recognizing low-level actions and high-level activities of interest. The former is usually the basis for the latter. This survey gives an overview of the most recent advances in human action recognition during the past several years, following a well-formed taxonomy proposed by a previous survey. From this state-of-the-art survey, researchers can view a panorama of progress in this area for future research.