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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2408.02803 |
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| _version_ | 1866913843079282688 |
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| author | Chen, Sherry X. Lim, Alex Christopher Liu, Yimeng Sen, Pradeep Sra, Misha |
| author_facet | Chen, Sherry X. Lim, Alex Christopher Liu, Yimeng Sen, Pradeep Sra, Misha |
| contents | Virtual try-on (VTO) applications aim to replicate the in-store shopping experience and enhance online shopping by enabling users to interact with garments. However, many existing tools adopt a one-size-fits-all approach when visualizing clothing items. This approach limits user interaction with garments, particularly regarding size and fit adjustments, and fails to provide direct insights for size recommendations. As a result, these limitations contribute to high return rates in online shopping. To address this, we introduce SiCo, a new online VTO system that allows users to upload images of themselves and interact with garments by visualizing how different sizes would fit their bodies. Our user study demonstrates that our approach significantly improves users' ability to assess how outfits will appear on their bodies and increases their confidence in selecting clothing sizes that align with their preferences. Based on our evaluation, we believe that SiCo has the potential to reduce return rates and transform the online clothing shopping experience. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_02803 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | SiCo: An Interactive Size-Controllable Virtual Try-On Approach for Informed Decision-Making Chen, Sherry X. Lim, Alex Christopher Liu, Yimeng Sen, Pradeep Sra, Misha Human-Computer Interaction Computer Vision and Pattern Recognition H.5.2; I.4.9 Virtual try-on (VTO) applications aim to replicate the in-store shopping experience and enhance online shopping by enabling users to interact with garments. However, many existing tools adopt a one-size-fits-all approach when visualizing clothing items. This approach limits user interaction with garments, particularly regarding size and fit adjustments, and fails to provide direct insights for size recommendations. As a result, these limitations contribute to high return rates in online shopping. To address this, we introduce SiCo, a new online VTO system that allows users to upload images of themselves and interact with garments by visualizing how different sizes would fit their bodies. Our user study demonstrates that our approach significantly improves users' ability to assess how outfits will appear on their bodies and increases their confidence in selecting clothing sizes that align with their preferences. Based on our evaluation, we believe that SiCo has the potential to reduce return rates and transform the online clothing shopping experience. |
| title | SiCo: An Interactive Size-Controllable Virtual Try-On Approach for Informed Decision-Making |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition H.5.2; I.4.9 |
| url | https://arxiv.org/abs/2408.02803 |