Year: 2020
Type: preprint
Abstract: This paper demonstrates how a Transformer Neural Network can be used to learn a Generative Model from a single path-based example image. We further show how a data set can be generated from the example image and how the model can be used to generate a large set of deviated images, which still represent the original image's style and concept.
Source: arXiv (Cornell University)
Authors: Wieluch, Sabine, Schwenker, Friedhelm
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3013854044