MV-Fashion: Towards Enabling Virtual Try-On and Size Estimation with Multi-View Paired Data
Existing 4D human datasets fall short for fashion-specific research, lacking either realistic garment dynamics or task-specific annotations. Synthetic datasets suffer from a realism gap, whereas real-world captures lack the detailed annotations and paired data required for virtual try-on (VTON) and size estimation tasks. To bridge this gap, we introduce MV-Fashion, a large-scale, multi-view video dataset engineered for domain-specific fashion analysis. MV-Fashion features 3,273 sequences (72.5 million frames) from 80 diverse subjects wearing 3-10 outfits each. It is designed to capture complex, real-world garment dynamics, including multiple layers and varied styling (e.g. rolled sleeves,...
| Authors | Hunor Laczkó, Libang Jia, Loc-Phat Truong et al. |
|---|---|
| Primary category | cs.CV |
| Published | 9 March 2026 |
| Last updated at source | 9 March 2026 |
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