[2308.13795] VIDES: Virtual Interior Design via Natural Language and Visual Guidance
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Computer Science > Computer Vision and Pattern Recognition

arXiv:2308.13795 (cs)
[Submitted on 26 Aug 2023]

Title:VIDES: Virtual Interior Design via Natural Language and Visual Guidance

Authors:Minh-Hien Le, Chi-Bien Chu, Khanh-Duy Le, Tam V. Nguyen, Minh-Triet Tran, Trung-Nghia Le
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Abstract:Interior design is crucial in creating aesthetically pleasing and functional indoor spaces. However, developing and editing interior design concepts requires significant time and expertise. We propose Virtual Interior DESign (VIDES) system in response to this challenge. Leveraging cutting-edge technology in generative AI, our system can assist users in generating and editing indoor scene concepts quickly, given user text description and visual guidance. Using both visual guidance and language as the conditional inputs significantly enhances the accuracy and coherence of the generated scenes, resulting in visually appealing designs. Through extensive experimentation, we demonstrate the effectiveness of VIDES in developing new indoor concepts, changing indoor styles, and replacing and removing interior objects. The system successfully captures the essence of users' descriptions while providing flexibility for customization. Consequently, this system can potentially reduce the entry barrier for indoor design, making it more accessible to users with limited technical skills and reducing the time required to create high-quality images. Individuals who have a background in design can now easily communicate their ideas visually and effectively present their design concepts. this https URL
Comments: Accepted to ISMAR 2023 (Poster paper)
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2308.13795 [cs.CV]
  (or arXiv:2308.13795v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2308.13795

Submission history

From: Trung Nghia Le [view email]
[v1] Sat, 26 Aug 2023 07:41:42 UTC (30,397 KB)
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