This paper presents Shape of You (SoY), an approach to improve the accuracy
of 3D body shape estimation for vision-based clothing recommendation systems.
While existing methods have successfully estimated 3D poses, there remains a
lack of work in precise shape estimation, particularly for diverse human
bodies. To address this gap, we propose two loss functions that can be readily
integrated into parametric 3D human reconstruction pipelines. Additionally, we
propose a test-time optimization routine that further improves quality. Our
method improves over the recent SHAPY method by 17.7% on the challenging SSP-3D
dataset. We consider our work to be a step towards a more accurate 3D shape
estimation system that works reliably on diverse body types and holds promise
for practical applications in the fashion industry.

本文提出了 Shape of You (SoY) 方法，旨在提高基于视觉的服装推荐系统中 3D 人体形状估计的精度。我们提出了两种损失函数和一种测试时间优化程序，可以轻松集成到参数化 3D 人体重建管道中，并在具有挑战性的 SSP-3D 数据集上将性能提高了 17.7%，在多样化人体类型方面的具有实际应用前景的更准确的 3D 形状估计系统迈出了一步。