Understanding User Experience with Virtual Try-On and Design Implications for Online Fashion Shopping
Suhyun Kim, Semin Lee, Jiseon Yang, Hayeon Kim, Uran Oh
Abstract
Online fashion shopping is booming, yet high return rates persist as actual size and fit do not meet shoppers’ expectations. Virtual Try-On (VTON), rendering garments on individuals’ body images, promises to reduce such issues. To understand VTON’s impact on shopping behaviors and experiences, we conducted user study with 24 participants where they were asked to explore and purchase clothing online and then shared their thoughts on satisfaction, similarity, and return intentions after wearing items. Results show that VTON reduced exploration time and product detail views, while enabling clearer expectations of fit before delivery. Importantly, participants often used VTON for final verification, while some sought to discover new styles, suggesting VTON should provide adaptive support according to users’ tendencies. Participants also emphasized fit accuracy, highlighting the need for technical improvements and reliability cues such as confidence scores. Building on these findings, we suggest design implications for integrating VTON into e-commerce.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 6a4d3916-d560-4bc4-8eaa-e8762fb9390fRelated papers
- VTON 360: High-Fidelity Virtual Try-On from Any Viewing DirectionZijian He, Yuwei Ning, Yipeng Qin, Guangrun Wang et al.CVPR 2025
- MOFA-VTON: More Fashion Possibilities with Fine-Grained Adaptations in Virtual Try-OnXiaoyu Han, Chenyang Wang, Jing Wang, Shunyuan Zheng et al.CVPR 2026
- Virtual Try-On with Pose-Garment Keypoints Guided InpaintingZhi Li, Pengfei Wei, Xiang Yin, Zejun Ma et al.ICCV 2023 · 37 citations
- M3D-VTON: A Monocular-to-3D Virtual Try-On NetworkFuwei Zhao, Zhenyu Xie, Michael Kampffmeyer, Haoye Dong et al.ICCV 2021 · 81 citations
- Per Garment Capture and Synthesis for Real-time Virtual Try-onToby Long Hin Chong, I-Chao Shen, Nobuyuki Umetani, Takeo IgarashiUIST 2021 · 9 citations
