mlsanityData to 7 Oct 2026

Size-Variable Virtual Try-On with Physical Clothes Size

arXiv 2412.06201 ↗First posted 9 Dec 2024cs.CV cs.GRcited by 1

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Abstract (arXiv)

This paper addresses a new virtual try-on problem of fitting any size of clothes to a reference person in the image domain. While previous image-based virtual try-on methods can produce highly natural try-on images, these methods fit the clothes on the person without considering the relative relationship between the physical sizes of the clothes and the person. Different from these methods, our method achieves size-variable virtual try-on in which the image size of the try-on clothes is changed depending on this relative relationship of the physical sizes. To relieve the difficulty in maintaining the physical size of the closes while synthesizing the high-fidelity image of the whole clothes, our proposed method focuses on the residual between the silhouettes of the clothes in the reference and try-on images. We also develop a size-variable virtual try-on dataset consisting of 1,524 images provided by 26 subjects. Furthermore, we propose an evaluation metric for size-variable virtual-try-on. Quantitative and qualitative experimental results show that our method can achieve size-variable virtual try-on better than general virtual try-on methods.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 43 references that are in the map. First posted on arXiv 9 Dec 2024.

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5 of 43 references.

References · 5

  1. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  2. 2021VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalizationcited by 287
  3. 2017GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibriumcited by 208
  4. 2019Self-Correction for Human Parsingcited by 179
  5. 2021TryOnGAN: Body-Aware Try-On via Layered Interpolationcited by 31

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