Deep Koalarization

Koalarization Architecture

Abstract

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.

Publication
Best project award, Deep Learning course at KTH, 2017
Federico Baldassarre
Federico Baldassarre
PhD Student in Deep Learning

My research focuses on explainability and reasoning in Deep Learning.

comments powered by Disqus