CVMMJun 22, 2022

A Fast Text-Driven Approach for Generating Artistic Content

arXiv:2208.01748v21 citationsh-index: 22
Originality Incremental advance
AI Analysis

This work addresses the need for more flexible and detailed artistic content generation, though it appears incremental as it builds on existing stylization methods.

The authors tackled the problem of generating visual art with flexible style parameters and improved detail, achieving a boost in generation speed and enhanced results through an artistic super-resolution module.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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