Banners are present in several forms and a person might be inspired by one or more of these. However, designing banners is a non-trivial task, especially for novices. Starting from a blank canvas can often be overwhelming, and exploring alternatives is time-consuming. In this paper, we propose an automatic approach to transfer a novice user's content into an example banner. Our algorithm begins with extracting the template of the example banner via a semantic segmentation approach. This is followed by an energy-based optimization framework to combine multiple design elements and arrive at an optimal layout. A crowd-sourced experiment comparing our automatic results against banners designed by creative professionals indicates the viability of the proposed work.
AI & Machine Learning
Computer Vision, Imaging & Video
Content Intelligence
Human Computer Interaction
24th ACM International Conference on Intelligent User Interfaces (IUI 2019)
Exemplar based Experience Transfer
Paridhi Maheshwari, Nitish Bansal, Surya Dwivedi, Rohan Kumar, Pranav Maneriker, Balaji Vasan Srinivasan
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