Splice, Focus and Relife: High-Resolution Periodic Pattern Generation

The printing and dyeing industry requires periodic and high-resolution patterns to ensure seamless designs on large fabric sections and high-quality final products. However, current manual approaches to pattern creation are time-consuming and labor-intensive. Leveraging powerful image generative models, such as Latent Diffusion Models (LDMs), offers a promising alternative, but challenges persist in generating strictly periodic and high-resolution patterns due to the inherent randomness and high computational demands of LDMs. In this paper, we propose a novel text-driven framework for generating periodic and high-resolution patterns. We introduce a new training-free Splice-and-Focus Mechanism, which enhances the model by constraining latent features and modifying the attention mechanism to produce natural and strictly periodic patterns. Additionally, we present a ReLife Pipeline, which integrates super-resolution and guided image synthesis to enhance pattern resolution while eliminating artifacts and distortions. Experimental results demonstrate that our framework produces patterns of superior quality.

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Publication Details

Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11043540
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Splice, Focus and Relife: High-Resolution Periodic Pattern Generation

Shuai Yang, Wenshuo Gao, Xiabin Lan, Jiaying Liu et al.
Manufacturing Process and Optimization
article

Splice, Focus and Relife: High-Resolution Periodic Pattern Generation

Shuai Yang, Wenshuo Gao, Xiabin Lan, Jiaying Liu, Luyao Zhang
article en

Abstract

The printing and dyeing industry requires periodic and high-resolution patterns to ensure seamless designs on large fabric sections and high-quality final products. However, current manual approaches to pattern creation are time-consuming and labor-intensive. Leveraging powerful image generative models, such as Latent Diffusion Models (LDMs), offers a promising alternative, but challenges persist in generating strictly periodic and high-resolution patterns due to the inherent randomness and high computational demands of LDMs. In this paper, we propose a novel text-driven framework for generating periodic and high-resolution patterns. We introduce a new training-free Splice-and-Focus Mechanism, which enhances the model by constraining latent features and modifying the attention mechanism to produce natural and strictly periodic patterns. Additionally, we present a ReLife Pipeline, which integrates super-resolution and guided image synthesis to enhance pattern resolution while eliminating artifacts and distortions. Experimental results demonstrate that our framework produces patterns of superior quality.

Peking University (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 79%
Manufacturing Process and Optimization
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Splice, Focus and Relife: High-Resolution Periodic Pattern Generation — Shuai Yang, Wenshuo Gao, et al. · (2025) | TGRS Research Map | TGRS