Reverse-Engineering Information Presentations: Recovering Hierarchical Grouping from Layouts of Visual Elements
This work addresses a challenge for researchers and designers in exploring layout structures and understanding design demographics, but it appears incremental as it builds on existing methods for grouping prediction.
The paper tackles the problem of automatically recovering hierarchical grouping from layouts of visual elements in information presentations, and the results show that their Transformer-based model and bottom-up algorithm are promising, as evaluated through a technical experiment and a user study with 30 designers.
Visual elements in an information presentation are often spatially and semantically grouped hierarchically for effective message delivery. Studying the hierarchical grouping information can help researchers and designers better explore layout structures and understand design demographics. However, recovering hierarchical grouping is challenging due to a large number of possibilities for compositing visual elements into a single-page design. This paper introduces an automatic approach that takes the layout of visual elements as input and returns the hierarchical grouping as output. To understand information presentations, we first contribute a dataset of 23,072 information presentations with diverse layouts to the community. Next, we propose our technique with a Transformer-based model to predict relatedness between visual elements and a bottom-up algorithm to produce the hierarchical grouping. Finally, we evaluate our technique through a technical experiment and a user study with 30 designers. The results show that the proposed technique is promising.