Young-Ho Kim, Jung-Hyun Han, Ye-Won Kwon, Yeon-Woo Kim, Yu-Da Hee
언어
영어(ENG)
URL
https://www.earticle.net/Article/A481201
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원문정보
초록
영어
This paper proposes and validates a reproducible generative AI framework for re-presenting and artistically extending Korean traditional folding screens in digital media. A curated set of 70 high-resolution minhwa landscape images is processed with CLIP-based near-duplicate pruning at a cosine threshold of 0.985 and ViT-based tagging with manual refinement. The model is fine-tuned with LoRA on Stable Diffusion v1.5, and a parameter search identifies an effective regime of 25 sampling steps and a CFG scale of 7.0 to 7.5. Subtle image-to-video motion with a fixed camera preserves contemplative aesthetics while enhancing immersion, yielding three exhibited artifacts: mountain, water, and an integrated scene. The study evidences a shift in digital heritage from preservation to generative extension and provides empirical support for LoRA-based style transfer in media art, while noting limitations in dataset size and genre scope and outlining future work in real-time interactivity and VR/AR deployment.
목차
Abstract 1. Introduction 2. Theoretical Background 2.1 Meanings and Formal Characteristics of Traditional Folding Screens 2.2 The Digital Transition of Traditional Art 2.3 The Convergence of Generative AI and Artistic Production 3. Methodology 3.1 Production Process for Folding Screens Using AI 3.2 AI Production Process 4. Results and Exhibition Case 4.1 Artifacts 4.2 Exhibition Case 5. Conclusion and Recommendations 5.1 Summary and Implications 5.2 Limitations and Future Work Acknowledgement References