Machine-Learning-Based Artistic Photo Manipulation and Stylization on Mobile Devices

Deep Learning is the new, and fast growing bread of systems based on artificial neural networks. These are phenomenal at learning patterns and generating new pattern that have the characteristics of the data the system was trained on. One of the main artistic and creative use of Deep Learning is to process images, pictures video. One typical task is that of style transfer by which the style of one image is used to shape the rendering of the one provided by the user. While most images are taken and manipulated by mobile devices, the deep learning algorithms required for style transfer and much more are not running on these more limited mobile hardware. This project aims to change this by porting Machine-Learning-based artistic photo manipulation and stylization on mobile devices.

Omid Alemi
Faculty Supervisor: 
Philippe Pasquier
British Columbia
Partner University: