We study and compare the human visual system and state-of-the-art deep neural networks on classification of distorted images. Different from previous works, we limit the display time to 100ms to test only the early mechanisms of the human visual system, without allowing time for any eye movements or other higher level processes. Our findings show that the human visual system still outperforms modern deep neural networks under blurry and noisy images. These findings motivate future research into developing more robust deep networks.
@article{arxiv.1710.04744,
title = {Can the early human visual system compete with Deep Neural Networks?},
author = {Samuel Dodge and Lina Karam},
journal= {arXiv preprint arXiv:1710.04744},
year = {2017}
}
Comments
Accepted as an oral paper at the Mutual Benefits of Cognitive and Computer Vision Workshop (held in conjunction with ICCV2017)