用手机生成鞋的3D模型，实现虚拟试穿
3D Reconstruction of Shoes for Augmented Reality
- 从2D图片生成3D鞋模，采用高斯点云加速建模
- 重建模型平均PSNR达32，分割精度IoU达0.95
- 适合电商、时尚领域做虚拟试穿，移动端即可运行
本文提出一种基于移动端的3D鞋类建模与增强现实（AR）方案，通过3D高斯泼溅技术提升建模效率。针对传统2D图片无法提供真实交互的问题，该框架可从2D图像生成逼真的3D鞋模，在智能手机上实现沉浸式AR体验。研究构建了一个包含3120张图像的定制鞋类分割数据集，最优分割模型达到0.95的交并比（IoU），3D重建平均峰值信噪比（PSNR）为32。结果表明，3D建模与AR技术有望彻底改变在线购物体验，并可推广至更广泛的时尚品类。
原文摘要 · Abstract (English)
This paper introduces a mobile-based solution that enhances online shoe shopping through 3D modeling and Augmented Reality (AR), leveraging the efficiency of 3D Gaussian Splatting. Addressing the limitations of static 2D images, the framework generates realistic 3D shoe models from 2D images, achieving an average Peak Signal-to-Noise Ratio (PSNR) of 32, and enables immersive AR interactions via smartphones. A custom shoe segmentation dataset of 3120 images was created, with the best-performing segmentation model achieving an Intersection over Union (IoU) score of 0.95. This paper demonstrates the potential of 3D modeling and AR to revolutionize online shopping by offering realistic virtual interactions, with applicability across broader fashion categories.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。