Deep Learning Architectures for Action Recognition

A review of the state of the art from 2014 to 2019

Abstract

Deep learning approaches have empirically demonstrated remarkable success in learning image representations for tasks like object recognition, image captioning, and semantic segmentation. Convolutional neural networks have enabled us to efficiently capture the hypothesis of spatial locality of data structure in images through parameter sharing convolutions, and local invariance-building max-pooling neurons. In this…