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Deep Learning in Mobile Sketch-Based Modelling

In this paper, performance of different deep learning methods is evaluated to improve sketch based modelling in the popular MagicToon mobile application, through their usage in the classification, contour detection, segmentation and automatic rigging stages. Results show that classification of browser-drawn sketches can be generalized to real life drawings. In comparison to previously proposed methods, detection performance for real drawings was improved using contour detection. Based on the results future improvements of sketch-based modelling using deep learning can be expected.