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Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization
2022
International Conference on Machine Learning
Image cartoonization is recently dominated by generative adversarial networks (GANs) from the perspective of unsupervised image-to-image translation, in which an inherent challenge is to precisely capture and sufficiently transfer characteristic cartoon styles (e.g., clear edges, smooth color shading, abstract fine structures, etc.). Existing advanced models try to enhance cartoonization effect by learning to promote edges adversarially, introducing style transfer loss, or learning to align
dblp:conf/icml/GaoZT22
fatcat:bjr5qzjp6nfehdsyppu5ka5nly