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Home/Retail & E-commerce/Home Outfit Virtual Try-On Dataset

Home Outfit Virtual Try-On Dataset

#image generation #style transfer #deep learning #virtual try-on #home decoration #e-commerce

Records: 5000 records
Size: 5G
Format: JPG/PNG/JSON
Provider: MOBIUSI INC
Updated: v1.02026-11-05

AI Analysis & Value Prop

The current retail e-commerce industry faces the challenge of users being unable to truly experience home outfits, especially when choosing furniture and decorations, making it difficult for users to judge their suitability. Existing solutions like static image display cannot meet the users' need for a real experience, leading to low conversion rates. Therefore, we have constructed this dataset to solve the selection difficulty of home outfits through virtual try-on technology. The dataset contains 20,000 synthetic images covering a variety of styles and categories, using high-quality image synthesis technology. Data collection is carried out through advanced image generation models, ensuring diversity and authenticity; at the same time, multiple rounds of annotation and expert review are implemented to ensure consistency and accuracy of annotations. The data is stored in JPG format and structured in JSON files for subsequent processing and analysis.

Overview

Dataset Insights

Preview

Sample Examples

d7af2845**.png|2160*2896|1.07 MB

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1748366f**.png|1936*2809|4.45 MB

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dda36a0e**.png|1854*2809|3.99 MB

Schema

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
clothing_type	string	The type of clothing in the home outfit, such as pajamas, loungewear, etc.
fabric_material	string	The material of the clothing fabric, such as cotton, silk, linen, etc.
color	string	The color of the clothing.
pattern	string	The pattern design on the clothing surface, such as stripes, plaid, solid color, etc.
size_label	string	The size label of the clothing, such as S, M, L, XL, etc.
style	string	The style of the clothing, such as minimalist, vintage, etc.
sleeve_length	string	The description of the sleeve length of the clothing, such as short sleeve, long sleeve, sleeveless, etc.
neckline_type	string	The type of neckline on the clothing, such as crew neck, V-neck, etc.
fit_type	string	The fit description of the clothing, such as slim fit, loose fit, etc.

Trust

Compliance Statement

Authorization Type

Proprietary - Commercial AI Training License (No Redistribution)

Commercial Use

Requires exclusive subscription or authorization contract (monthly or per-invocation charging)

Privacy and Anonymization

No PII, no real company names, simulated scenarios follow industry standards

Compliance System

Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

FAQ

Frequently Asked Questions

What is the Home Loungewear Virtual Try-On Dataset?: The Home Loungewear Virtual Try-On Dataset is a multimodal dataset designed to provide virtual try-on solutions for loungewear, helping the e-commerce industry enhance user experience.

Which industry does the Home Loungewear Virtual Try-On Dataset apply to?: This dataset is used in the retail industry, specifically in e-commerce, to enhance the user experience when purchasing loungewear.

How does the Home Loungewear Virtual Try-On Dataset improve user experience?: By offering virtual try-on solutions for loungewear, users can preview the fit before purchasing, enhancing shopping satisfaction and reducing return rates.

What is the role of a multimodal dataset in virtual try-on for loungewear?: A multimodal dataset integrates image processing technologies to deliver realistic virtual try-on experiences for loungewear.

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Cite this Work

@dataset{Mobiusi2025,
  title={Home Outfit Virtual Try-On Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/48de58abdeb88f9da568e43d984264d5?dataset_scene_id=9},
  urldate={2025-09-15},
  keywords={virtual try-on dataset, home outfit, image synthesis, e-commerce, retail e-commerce},
  version={1.0}
}

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