CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON


Matiur Rahman Minar
Heejune Ahn

Seoul National University of Science and Technology

ACCV 2020
Asian Conference on Computer Vision

[paper]
[supplementary]
[video]
[bibtex]


We proposed a novel hybrid and fully automatic method for 3D clothing reconstruction from single image and applying it to image-based virtual try-on (VTON) for fashion clothing, which generates realistically deformed try-on results with the highest possible quality.

Virtual clothing try-on, transferring a clothing image onto a target person image, is drawing industrial and research attention. Both 2D image-based and 3D model-based methods proposed recently have their benefits and limitations. Whereas 3D model-based methods provide realistic deformations of the clothing, it needs a difficult 3D model construction process and cannot handle the non-clothing areas well. Imagebased deep neural network methods are good at generating disclosed human parts, retaining the unchanged area, and blending image parts, but cannot handle large deformation of clothing. In this paper, we propose CloTH-VTON that utilizes the high-quality image synthesis of 2D image-based methods and the 3D model-based deformation to the target human pose. For this 2D and 3D combination, we propose a novel 3D cloth reconstruction method from a single 2D cloth image, leveraging a 3D human body model, and transfer to the shape and pose of the target person. Our cloth reconstruction method can be easily applied to diverse cloth categories. Our method produces final try-on output with naturally deformed clothing and preserving details in high resolution.




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Citation

Matiur Rahman Minar and Heejune Ahn "CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON." In: Asian Conference on Computer Vision (ACCV), 2020.

@InProceedings{Minar_CLOTHVTON_2020_ACCV,
    title={CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON},
    author={Minar, Matiur Rahman and Ahn, Heejune},
    booktitle = {Asian Conference on Computer Vision (ACCV)},
    year={2020}
}





Acknowledgements

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