State of Deep Learning in Computer Vision

Part I - ConvNet Architectures

This article is an extension of a talk I gave at the Czech Technical University (CTU) in July 2017. We surveyed around a hundred deep learning papers and selected the most interesting and important outcomes that will help you to understand the impact of deep learning in computer vision. Our talk touched on three topics: novel architectures of Convolutional Neural Networks (ConvNets), the Attention Mechanism, and Video Classification. These are the most critical components of our deep learning system. We use these at the ShowmaxLab at CTU to better understand movies. This is the first of two parts focused on ConvNets, the second one will cover the Attention. »