  We review some of the most recent approaches to colorize gray-scale images
using deep learning methods. Inspired by these, we propose a model which
combines a deep Convolutional Neural Network trained from scratch with
high-level features extracted from the Inception-ResNet-v2 pre-trained model.
Thanks to its fully convolutional architecture, our encoder-decoder model can
process images of any size and aspect ratio. Other than presenting the training
results, we assess the "public acceptance" of the generated images by means of
a user study. Finally, we present a carousel of applications on different types
of images, such as historical photographs.
