Restyling Images with the Bangladeshi Paintings Using Neural Style Transfer: A Comprehensive Experiment, Evaluation, and Human Perspective
Manal, Ali Hasan Md. Linkon, Md. Mahir Labib, Marium-E-Jannat, Md, Saiful Islam

TL;DR
This paper explores neural style transfer applied to Bangladeshi paintings, evaluating aesthetic preferences through human studies and analyzing the potential for cultural and practical applications.
Contribution
It is the first comprehensive study applying NST to Bangladeshi artwork, including qualitative and quantitative evaluation from human perspectives.
Findings
Human evaluations show positive aesthetic preferences for NST stylized Bangladeshi paintings.
The study provides insights into the effectiveness of NST algorithms on traditional Bangladeshi art.
Potential applications in mobile UI/GUI and material translation are discussed.
Abstract
In today's world, Neural Style Transfer (NST) has become a trendsetting term. NST combines two pictures, a content picture and a reference image in style (such as the work of a renowned painter) in a way that makes the output image look like an image of the material, but rendered with the form of a reference picture. However, there is no study using the artwork or painting of Bangladeshi painters. Bangladeshi painting has a long history of more than two thousand years and is still being practiced by Bangladeshi painters. This study generates NST stylized image on Bangladeshi paintings and analyzes the human point of view regarding the aesthetic preference of NST on Bangladeshi paintings. To assure our study's acceptance, we performed qualitative human evaluations on generated stylized images by 60 individual humans of different age and gender groups. We have explained how NST works for…
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Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · Advanced Image Processing Techniques · Image Enhancement Techniques
