Advancing Persistent Character Generation: Comparative Analysis of Fine-Tuning Techniques for Diffusion Models

In the evolving field of artificial intelligence, fine-tuning diffusion models is crucial for generating contextually coherent digital characters across various media. This paper examines four advanced fine-tuning techniques: Low-Rank Adaptation (LoRA), DreamBooth, Hypernetworks, and Textual Inversi...

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Hlavní autoři:	Luca Martini, Saverio Iacono, Daniele Zolezzi, Gianni Viardo Vercelli
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-09-01
Edice:	AI
Témata:	AI-driven digital characters diffusion models fine-tuning neural networks text-to-image synthesis
On-line přístup:	https://www.mdpi.com/2673-2688/5/4/88
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