Towards Squeezing-Averse Virtual Try-on via Sequential Deformation
Abstract
In this paper, we first investigate a visual quality degradation problem observed in recent high-resolution virtual try-on approach. The tendency is empirically found that the textures of clothes are squeezed at the sleeve, as visualized in the upper row of Fig.1(a). A main reason for the issue arises from a gradient conflict between two popular losses, the Total Variation (TV) and adversarial losses. Specifically, the TV loss aims to disconnect boundaries between the sleeve and torso in a warped clothing mask, whereas the adversarial loss aims to combine between them. Such contrary objectives feedback the misaligned gradients to a cascaded appearance flow estimation, resulting in undesirable squeezing artifacts. To reduce this, we propose a Sequential Deformation (SD-VITON) that disentangles the appearance flow prediction layers into TV objective-dominant (TVOB) layers and a task-coexistence (TACO) layer. Specifically, we coarsely fit the clothes onto a human body via the TVOB layers, and then keep on refining via the TACO layer. In addition, the bottom row of Fig.1(a) shows a different type of squeezing artifacts around the waist. To address it, we further propose that we first warp the clothes into a tucked-out shirts style, and then partially erase the texture from the warped clothes without hurting the smoothness of the appearance flows. Experimental results show that our SD-VITON successfully resolves both types of artifacts and outperforms the baseline methods. Source code will be available at https://github.com/SHShim0513/SD-VITON.
Cite
Text
Shim et al. "Towards Squeezing-Averse Virtual Try-on via Sequential Deformation." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I5.28288Markdown
[Shim et al. "Towards Squeezing-Averse Virtual Try-on via Sequential Deformation." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/shim2024aaai-squeezing/) doi:10.1609/AAAI.V38I5.28288BibTeX
@inproceedings{shim2024aaai-squeezing,
title = {{Towards Squeezing-Averse Virtual Try-on via Sequential Deformation}},
author = {Shim, Sang-Heon and Chung, Jiwoo and Heo, Jae-Pil},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2024},
pages = {4856-4863},
doi = {10.1609/AAAI.V38I5.28288},
url = {https://mlanthology.org/aaai/2024/shim2024aaai-squeezing/}
}