Research on the Teaching Path of Home Space Design Based on Stable Diffusion Intelligent Generation Technology in the Digital Economy Era
Pages 229 - 238
Abstract
Driven by the wave of digital economy, home space design is facing the dual challenges of technology and methods. The rise of Stable Diffusion intelligent generation technology has brought revolutionary opportunities for home space design teaching. This research is devoted to exploring a new teaching path of home space design based on Stable Diffusion technology from the perspective of the latest technology. Through an in-depth analysis of the characteristics of the digital economy era and the application of technology, this paper examines the limitations of traditional home space design teaching, and discusses how technology enables the improvement of teaching quality. This study aims to provide cutting-edge theoretical support and practical guidance for the reform and innovation of home space design teaching, and promote the overall improvement of education quality in this field.
References
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Ding C, Liu C, Zheng C, Digital economy, technological innovation and high-quality economic development: Based on spatial effect and mediation effect [J]. Sustainability, 2021, 14(1):216.
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Sinha, M.; Fukey, L.N. Sustainable Interior Designing in the 21st Century—A Review. ECS Trans. 2022, 107, 6801.
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Borji, A. Generated faces in the wild: Quantitative comparison of stable diffusion, midjourney and dall-e 2. arXiv 2022, arXiv:2204.06125.
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- Research on the Teaching Path of Home Space Design Based on Stable Diffusion Intelligent Generation Technology in the Digital Economy Era
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Published In
May 2024
618 pages
ISBN:9798400718267
DOI:10.1145/3675249
Copyright © 2024 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
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Association for Computing Machinery
New York, NY, United States
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Published: 01 August 2024
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ICCMT 2024
ICCMT 2024: 2024 International Conference on Computer and Multimedia Technology
May 24 - 26, 2024
Sanming, China
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