SAMStyler: Enhancing Visual Creativity With Neural Style Transfer and Segment Anything Model (SAM)

SAMStyler: Enhancing Visual Creativity With Neural Style Transfer and Segment Anything Model (SAM)

Neural Style Transfer (NST) is a popular technique of computer vision where the content of an image is blended with the style of another, which results in a fused image with certain properties of both original images. This approach has practical applications in various domains and has garnered signi...

Bibliografske podrobnosti
Main Authors:	Konstantinos Psychogyios, Helen C. Leligou, Filisia Melissari, Stavroula Bourou, Zacharias Anastasakis, Theodore Zahariadis
Format:	Article
Jezik:	English
Izdano:	IEEE 2023-01-01
Serija:	IEEE Access
Teme:	Segment anything model segment anything segmentation machine learning style transfer
Online dostop:	https://ieeexplore.ieee.org/document/10250775/

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