We train on a million images, with simulated user inputs. To guide the user towards efficient input selection, the system recommends likely colors based on the input image and current user inputs. The colorization is performed in a single feed-forward pass, enabling real-time use. Even with randomly simulated user inputs, we show that the proposed system helps novice users quickly create realistic colorizations, and show large improvements in colorization quality with just a minute of use.

Source: Real-Time User-Guided Image Colorization with Learned Deep Priors. In SIGGRAPH, 2017.