Research Paper Analysis
Research on the Innovation Path of Yangjiabu New Year's Paintings in Packaging Design Based on AIGC
This study explores Shandong Yangjiabu woodblock prints in traditional packaging design and the practical use of artificial intelligence generated content (AIGC) technology to adapt print elements and innovate packaging design. We can digitally extract and reconstruct Yangjiabu New Year's Paintings for intelligent packaging design by developing a closed-loop model with "data-driven analysis, feature evaluation, intelligent generation, and optimization iteration," and integrating natural language processing with text image generation technology. This method presents a new way to preserve non-heritage culture while highlighting the practicality of intelligent packaging design and modern interpretations of historic components. The intelligent innovation of packaging design and the contemporary transformation of historic features gain practical significance.
Executive Impact & Key Metrics
AIGC technology offers a transformative approach for preserving traditional art forms like Yangjiabu New Year's Paintings by enabling their adaptation into modern packaging. By digitizing, intelligently generating, and optimizing design elements, AIGC addresses challenges of cultural gene retention and innovative expression. This method streamlines design, enhances creativity, and ensures cultural relevance in contemporary consumer markets, opening new avenues for non-heritage cultural transmission and commercial viability.
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Reduction in Design Iteration Time
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Increase in Design Variants
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Improved Cultural Integration Score
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The paper details the underlying AIGC technologies, specifically Generative Adversarial Networks (GANs) and text-to-image models like Midjourney. It explains how these tools facilitate efficient image generation, style migration, and batch creation, enabling the innovative adaptation of traditional art forms.
This section outlines the 'data-driven analysis, feature evaluation, intelligent generation, and optimization iteration' closed-loop model. It describes the process of digitally extracting, reconstructing, and adapting Yangjiabu elements, integrating natural language processing with text-image generation to innovate packaging design.
The study emphasizes how AIGC helps preserve non-heritage culture by modernizing historical components for contemporary contexts. It addresses the challenges of rigid traditional themes and visual styles, promoting a synergistic development of non-genetic inheritance through intelligent design.
Synergistic Growth
of Non-heritage Heritage & Design Intelligence via AIGC
Enterprise Process Flow
Data-Driven Analysis
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Feature Evaluation
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Intelligent Generation
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Optimization Iteration
| Feature | Traditional Design | AIGC-Driven Design |
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| Cultural Adaptation |
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| Youth Engagement |
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Yangjiabu New Year's Paintings in Packaging
The study showcases the application of AIGC to transform Yangjiabu New Year's Paintings into modern packaging designs. By reinterpreting motifs like the 'Whip Mace Door God' with vector flattening and cross-stylistic fusion, the designs achieve visual simplicity and impact. This process overcomes the limitations of traditional woodcut aesthetics, adapting them for everyday fast food packaging while preserving cultural essence.
Key Achievement: Successful integration of traditional art into modern consumer products, balancing 'creative expression' with 'living legacy'.
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Estimated Annual Savings
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Hours Reclaimed Annually
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