@inproceedings{ce3288958a014a6387e076107acc8228,
title = "A Style-Based Caricature Generator",
abstract = "A facial caricature is a creation of new artistic and exaggerated faces which translates into a real image to convey sarcasm or humor while keeping the identity of the subject. In this work, we proposed a new way to create caricatures by exaggerating facial features like the eyes and mouth while keeping the facial contour intact and a realistic style. Our method can be categorized into two steps. First, the facial exaggeration process transformed faces into caricature face images while maintaining facial contours. Second, the appearance style generator is trained in unpaired using the generated caricature faces to produce a facial caricature that can change to any realistic style of our preference. Experimental results show our model produces more realistic and disentangled caricature images as compared to some of the previous methods. Our method can also generate caricature images from real images.",
keywords = "Caricature, Generative Adversarial Network, Style Generator",
author = "Lamyanba Laishram and Muhammad Shaheryar and Lee, {Jong Taek} and Jung, {Soon Ki}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.; Proceedings of the 29th International Workshop on Frontiers of Computer Vision, IW-FCV 2023 ; Conference date: 20-02-2023 Through 22-02-2023",
year = "2023",
doi = "10.1007/978-981-99-4914-4_6",
language = "English",
isbn = "9789819949137",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "71--82",
editor = "Inseop Na and Go Irie",
booktitle = "Frontiers of Computer Vision - 29th International Workshop, IW-FCV 2023, Revised Selected Papers",
address = "Germany",
}