# From 2D to 3D Geodesic-based Garment Matching

arXiv: https://arxiv.org/abs/1809.08064 · HTML: https://mlsanity.com/paper/1809.08064/

## Key facts

- Cited by 1 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 21 Sep 2018.

## Built on by (most cited first, 1 of 1)

- [Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration](https://mlsanity.com/paper/2203.02227/) (2022)

## Abstract (arXiv)

A new approach for 2D to 3D garment retexturing is proposed based on Gaussian mixture models and thin plate splines (TPS). An automatically segmented garment of an individual is matched to a new source garment and rendered, resulting in augmented images in which the target garment has been retextured by using the texture of the source garment. We divide the problem into garment boundary matching based on Gaussian mixture models and then interpolate inner points using surface topology extracted through geodesic paths, which leads to a more realistic result than standard approaches. We evaluated and compared our system quantitatively by mean square error (MSE) and qualitatively using the mean opinion score (MOS), showing the benefits of the proposed methodology on our gathered dataset.