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Cartoonizer: Convert Images and Videos to Cartoon-Style Images and Videos

Authors :
Rajatha, S.
Makkigadde, Anusha Shrikant
Kanchan, Neha L.
Sapna
Bhat, K. Janardhana
Rajatha, S.
Makkigadde, Anusha Shrikant
Kanchan, Neha L.
Sapna
Bhat, K. Janardhana
Source :
International Journal of Research in Engineering, Science and Management; Vol. 4 No. 7 (2021); 275-278; 2581-5792
Publication Year :
2021

Abstract

The process of converting real-life high-quality pictures and videos into practical cartoon images and videos is known as cartoonization. The saved model decomposes uploaded images and videos into three different cartoon depictions as surface representation, structure representation, texture representation, which further instructs the network optimization to generate cartoon image. It helps to sleek the image, filter the qualities, transforming it to sketches, and translating the output from a domain to another. The extracted outputs are fed to a Generative Neural Networks (GAN) framework, which helps to improve our problem making the solution more flexible and varied, where GAN stands for Generative Adversarial Network is used to transform uploaded images (snapshots) to the finest cartooned image. Using the loss function and its two types named as Adversarial loss and Content Loss, we gained a flexible as well as a clear edge defined images.

Details

Database :
OAIster
Journal :
International Journal of Research in Engineering, Science and Management; Vol. 4 No. 7 (2021); 275-278; 2581-5792
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1376700747
Document Type :
Electronic Resource