Interactive Cartoonization with Controllable Perceptual Factors

Cartoonization is a task that renders natural photos into cartoon styles. Previous deep cartoonization methods only have focused on end-to-end translation, which may hinder editability. Instead, we propose a novel solution with editing features of texture and color based on the cartoon creation proc...

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Bibliographic Details
Published in2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) pp. 16827 - 16835
Main Authors Ahn, Namhyuk, Kwon, Patrick, Back, Jihye, Hong, Kibeom, Kim, Seungkwon
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2023
Subjects
Aerospace electronics
Computer architecture
Computer vision
Decoding
Image and video synthesis and generation
Image color analysis
Pattern recognition
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Summary:Cartoonization is a task that renders natural photos into cartoon styles. Previous deep cartoonization methods only have focused on end-to-end translation, which may hinder editability. Instead, we propose a novel solution with editing features of texture and color based on the cartoon creation process. To do that, we design a model architecture to have separate decoders, texture and color, to decouple these attributes. In the texture decoder, we propose a texture controller, which enables a user to control stroke style and abstraction to generate diverse cartoon textures. We also introduce an HSV color augmentation to induce the networks to generate diverse and controllable color translation. To the best of our knowledge, our work is the first deep approach to control the cartoonization at inference while showing profound quality improvement over to baselines.
ISSN:2575-7075
DOI:10.1109/CVPR52729.2023.01614