Interior design display based on NST algorithm and AR

This study proposes an interior design display model based on a neural style transfer algorithm and augmented reality technology to address the current time-consuming, single-function, and high information requirements of interior design display methods. This model combines virtual reality overlay technology to enhance users’ visual and auditory interaction experience, reasonably allocates the weights of the style loss function and content loss function, and reduces spatial loss. In the experiment, the model training achieved a loss value of 162,091.33 and a space loss rate of more than 1%. In practical applications, a reality reproduction score of 8.7 was achieved, with a peak signal-to-noise ratio higher than 50 dB, indicating a relatively small loss of image quality. Furthermore, the click-through rate of users has increased by 0.115, and the purchase conversion rate has increased by 0.270, indicating that this model has significant effectiveness and advancement in interior design displays.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-07-19
DOI
https://doi.org/10.1177/14727978251361518
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
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article

Interior design display based on NST algorithm and AR

Journal of Computational Methods in Sciences and Engineering
Hydrology and Drought Analysis
article

Interior design display based on NST algorithm and AR

article en

Abstract

This study proposes an interior design display model based on a neural style transfer algorithm and augmented reality technology to address the current time-consuming, single-function, and high information requirements of interior design display methods. This model combines virtual reality overlay technology to enhance users’ visual and auditory interaction experience, reasonably allocates the weights of the style loss function and content loss function, and reduces spatial loss. In the experiment, the model training achieved a loss value of 162,091.33 and a space loss rate of more than 1%. In practical applications, a reality reproduction score of 8.7 was achieved, with a peak signal-to-noise ratio higher than 50 dB, indicating a relatively small loss of image quality. Furthermore, the click-through rate of users has increased by 0.115, and the purchase conversion rate has increased by 0.270, indicating that this model has significant effectiveness and advancement in interior design displays.

Journal of Computational Methods in Sciences and Engineering
Zhengzhou University of Industrial Technology (CN)
Openalex Percentile: Top 57%
Hydrology and Drought Analysis
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Interior design display based on NST algorithm and AR · Journal of Computational Methods in Sciences and Engineering (2025) | TGRS Research Map | TGRS