Palette Based Image Recolouring using Neural Networks

18th October 2018

Proposed by Mairéad Grogan
Email: mgrogan at

Image recolouring is an important application in computer vision, and can be used by photographers when editing images, as a post processing step in the film industry to change the look and feel of a scene, or by users of apps such as Instagram or Snapchat when they apply filters to images. Palette based image recolouring is a popular method for image recolouring. Given an input image, a palette of colours is generated that represents the colours in an image. The user can then edit this palette of colours to create the desired colour changes in the image. However, unexpected colour changes can be created, for example if a light colour is changed to a very dark colour, artifacts can be created. This project proposes using a neural network approach to learn the best recolouring result given the original image, it’s original palette and the new user defined palette.

PaletteNet: Image Recolorization with Given Color Palette, Junho Cho, Sangdoo Yun, Kyoungmu Lee, Jin Young Choi.  2017 IEEE Conference on  Computer Vision and Pattern Recognition Workshops (CVPRW) .
Link to pdf: