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A Method for Automatically Animating Children's Drawings of the Human Figure

ACM Transactions on Graphics (TOG), 2023
7 March 2023
H. Smith
Qingyuan Zheng
Yifei Li
Somya Jain
Jessica Hodgins
ArXiv (abs)PDFHTML
Abstract

Children's drawings have a wonderful inventiveness, creativity, and variety to them. We present a system that automatically animates children's drawings of the human figure, is robust to the variance inherent in these depictions, and is simple and straightforward enough for anyone to use. We demonstrate the value and broad appeal of our approach by building and releasing the Animated Drawings Demo, a freely available public website that has been used by millions of people around the world. We present a set of experiments exploring the amount of training data needed for fine-tuning, as well as a perceptual study demonstrating the appeal of a novel "twisted perspective" retargeting technique. Finally, we introduce the Amateur Drawings Dataset, a first-of-its-kind annotated dataset, collected via the public demo, containing ~180,000 amateur drawings and corresponding user-accepted character bounding box, segmentation mask, and joint location annotations.

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