A collection of Deep Learning based Image Colorization papers and corresponding source code/demo program, including Automatic and User Guided (i.e. with User Interaction) colorization, as well as video colorization.
To solve this problem, we propose a two-stage deep colorization method allowing users to control the results by flexibly setting global inputs and local inputs.
We propose a deep learning approach for user-guided image colorization. The system directly maps a grayscale image, along with sparse, local user ``hints" to an output colorization with a Convolutional Neural Network (CNN).
In this paper, a comprehensive review of recent DLIC approaches from algorithm classification to existing challenges is provided to facilitate researchers’ in-depth understanding of DLIC.
