A Method for Animating Children's Drawings of the Human Figure
March 07, 2023 Β· Declared Dead Β· π ACM Transactions on Graphics
"No code URL or promise found in abstract"
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Authors
Harrison Jesse Smith, Qingyuan Zheng, Yifei Li, Somya Jain, Jessica K. Hodgins
arXiv ID
2303.12741
Category
cs.CV: Computer Vision
Cross-listed
cs.GR
Citations
40
Venue
ACM Transactions on Graphics
Last Checked
5 months ago
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 over 178,000 amateur drawings and corresponding user-accepted character bounding boxes, segmentation masks, and joint location annotations.
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