Advancements in Three-Dimensional Virtual Try-On Technology
- DOI
- 10.2991/978-94-6463-504-1_32How to use a DOI?
- Keywords
- 3D Virtual Fitting; 3D Human Scanning; 3D Modeling; Deep Learning
- Abstract
With the advent of the digital age and the widespread adoption of online shopping, 3D virtual fitting technology has emerged, fostering the integration of fashion and e-commerce and enhancing consumers’ online shopping experiences. This paper reviews the development, key technologies, and applications of 3D virtual fitting technology across various domains. First, it explores the characteristics, advantages, and disadvantages of 3D human scanning technologies, including contact and non-contact measurement methods. It then elucidates the primary strategies for human body loading and clothing 3D modeling, encompassing traditional 3D visual modeling and deep learning methods. The paper outlines the critical applications and technical challenges in enhancing the realism and user experience of virtual fitting. Finally, it anticipates future trends in 3D virtual fitting technology, focusing on algorithm optimization, hardware advancements, and its role in promoting sustainable development.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Tong Zhao AU - Qingfu Li AU - Xiaoyi Wang PY - 2024 DA - 2024/08/31 TI - Advancements in Three-Dimensional Virtual Try-On Technology BT - Proceedings of the 2024 3rd International Conference on Information Economy, Data Modelling and Cloud Computing (ICIDC 2024) PB - Atlantis Press SP - 332 EP - 343 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-504-1_32 DO - 10.2991/978-94-6463-504-1_32 ID - Zhao2024 ER -