DUES-adapt: Exploring distributed user experience with neural UI adaptation

Abstract

Developers spend a great deal of time to adapt UI to different devices. By learning experience from massive number of human designed UI products, the adaptation work could be finished by machines. To this end, we introduce DUES-Adapt, an AI based UI adaptation system, and showcase in this demonstration. Given an input UI, DUES-Adapt parses the basic UI elements and employs the parsing results to generate a reasonable and aesthetic layout for a target device. The two AI problems, UI parsing and layout generation, are solved using deep neural network model and trained with over 10K app instances collected from mainstream Android markets. In the demonstration, we show a number of cases covering many apps like music, maps, fitness and different target terminals such as tablet, smartwatch, TV etc.