# Very Deep Convolutional Networks for Large-Scale Image Recognition

**Authors:** Karen Simonyan, Andrew Zisserman  
**arXiv:** [1409.1556](https://arxiv.org/abs/1409.1556)  
**Date:** 2014-09-04  
**Summary page:** https://www.summarizepaper.com/fr/paper/1409.1556v1/

## Abstract

In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluation of networks of increasing depth, which shows that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 weight layers. These findings were the basis of our ImageNet Challenge 2014 submission, where our team secured the first and the second places in the localisation and classification tracks respectively.