A short analysis of BigColor for image colorization.

Abstract

This work analyzes the BigColor method, a fully automatic colorization approach that aims to meet the challenge of providing realistic and vivid colorization for complex and diverse images in real-world scenarios. The method is a BigGAN-inspired encoder-generator network, using a spatial feature map, enabling single forward-pass colorization, supporting arbitrary input resolutions, and producing multimodal colorization results. We provide a short analysis of the method’s results and highlight some limitations alongside its achievements.