2022/06/22 by Marian Lupaşcu, Marian Lupascu, Lupascu, Marian +7 · 1 voice
Computer Science · #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Multimedia (cs.MM) #Video Analysis and Summarization #cs.CV #cs.MM
paper · pdf · doi:10.48550/arxiv.2208.01748
openalex publication_date 2022/06/22 · arxiv published 2022/06/22 · arxiv updated 2025/08/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this work, we propose a complete framework that generates visual art. Unlike previous stylization methods that are not flexible with style parameters (i.e., they allow stylization with only one style image, a single stylization text or stylization of a content image from a certain domain), our method has no such restriction. In addition, we implement an improved version that can generate a wide range of results with varying degrees of detail, style and structure, with a boost in generation speed. To further enhance the results, we insert an artistic super-resolution module in the generative pipeline. This module will bring additional details such as patterns specific to painters, slight brush marks, and so on.