# An Analysis of Deep Neural Networks with Attention for Action Recognition from a Neurophysiological Perspective

## TL;DR

This paper reviews three deep learning methods for action recognition, comparing them from a neurophysiological perspective to explore analogies with human brain hypotheses.

## Contribution

It provides a comparative analysis linking deep learning methods for action recognition to neurophysiological theories of brain function.

## Key findings

- Identifies analogies between deep learning models and brain hypotheses
- Highlights similarities in processing mechanisms
- Suggests neurophysiological insights for improving models

## Abstract

We review three recent deep learning based methods for action recognition and present a brief comparative analysis of the methods from a neurophyisiological point of view. We posit that there are some analogy between the three presented deep learning based methods and some of the existing hypotheses regarding the functioning of human brain.