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  4. UISketch: A Large-Scale Dataset of UI Element Sketches
 
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2021
Conference Paper
Title

UISketch: A Large-Scale Dataset of UI Element Sketches

Abstract
This paper contributes the first large-scale dataset of 17,979 hand-drawn sketches of 21 UI element categories collected from 967 participants, including UI/UX designers, front-end developers, HCI, and CS grad students, from 10 different countries. We performed a perceptual study with this dataset and found out that UI/UX designers can recognize the UI element sketches with ~96% accuracy. To compare human performance against computational recognition methods, we trained the state-of-the-art DNN-based image classification models to recognize the UI elements sketches. This study revealed that the ResNet-152 model outperforms other classification networks and detects unknown UI element sketches with 91.77% accuracy (chance is 4.76%). We have open-sourced the entire dataset of UI element sketches to the community intending to pave the way for further research in utilizing AI to assist the conversion of lo-fi UI sketches to higher fidelities.
Author(s)
Pandian, Vinoth
Suleri, Sarah
Jarke, Matthias  
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Mainwork
CHI 2021, Conference on Human Factors in Computing Systems. Proceedings  
Conference
Conference on Human Factors in Computing Systems (CHI) 2021  
DOI
10.1145/3411764.3445784
Language
English
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
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