Abstract
Shadow performs an important role in the image, which can enhance the image effect and convey important visual clues. We propose a method based on deep learning to automatically generate stylized shadows for line drawings. Based on StarGAN, a shadow generation adversarial network (ShadowGAN) is designed, which can automate the creation of stylized shadows with different light directions. This method defines eight light directions. Users can select one of the eight light directions around the 2D image to specify the light source according to the encoding of the light direction, and generate the shadow corresponding to the light direction. We use a new dataset containing line drawings with shadows and label information corresponding to the light direction. Experiments show that our method can generate stylized shadows for line drawing with satisfactory quality, which can simplify the user’s workflow, and save the time of drawing line drawing shadows.
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Xue, H., Kang, C. (2023). ShadowGAN for Line Drawings Shadow Generation. In: Iliadis, L., Papaleonidas, A., Angelov, P., Jayne, C. (eds) Artificial Neural Networks and Machine Learning – ICANN 2023. ICANN 2023. Lecture Notes in Computer Science, vol 14262. Springer, Cham. https://doi.org/10.1007/978-3-031-44201-8_25
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