Problem
Research questions and friction points this paper is trying to address.
Generates diverse visual art from text input
Overcomes single-style limitations in previous methods
Enhances artistic details and generation speed
A Fast Text-Driven Approach for Generating Artistic Content
🤖 AI Summary
Existing art image generation methods are constrained by single-style inputs—such as a single reference image or domain-specific text—resulting in coarse-grained and inflexible style control. This work introduces the first end-to-end text-driven artistic image generation framework enabling multi-granular style disentanglement: a tunable style encoder accepts arbitrary textual style descriptions and independently modulates structural layout, fine-grained details, and global style intensity. We further propose the first art-guided super-resolution module, which injects painter-level brushstroke and texture features into diffusion outputs. Built upon a text-conditioned diffusion backbone, our method integrates a lightweight super-resolution network and an accelerated sampling strategy. Extensive evaluations demonstrate state-of-the-art performance across FID, LPIPS, and human assessments—achieving superior generation quality, diversity, and real-time inference capability.
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Flexible text-driven artistic content generation
Improved version with varied detail and speed
Artistic super-resolution for enhanced painterly details
🔎 Similar Papers
No similar papers found.
