Underwear Occlusion Image Dataset
#Image Classification #Object Detection #Product Display #Visual Recognition #E-commerce Analysis
- 20000 records
- 1.8G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-22
AI Analysis & Value Prop
The retail e-commerce industry is currently facing challenges with visual recognition systems that struggle to accurately identify and classify products that are partially occluded. Existing solutions often overlook the nuances of occluded images, leading to poor classification results. This dataset aims to address these shortcomings by providing a comprehensive collection of images featuring occluded underwear, thus enabling more robust training of models for visual recognition tasks. The data is collected using high-resolution cameras in controlled lighting conditions to ensure clarity and detail. Quality control measures include multi-round annotations, consistency checks among annotators, and expert reviews to maintain a high standard. The images are organized in a structured directory format and stored in JPG format for easy access and processing.
Dataset Insights
Sample Examples
b8f3a32d**.png|1704*1500|1.82 MB
2b0e6878**.png|1021*1500|761.83 KB
74956ad9**.png|867*1500|1.15 MB
948d2430**.png|1517*1500|1.76 MB
517659d8**.png|1440*1500|1.39 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_count | int | The total number of targets identified in the image. |
| object_type | string | The type of each target in the image, such as bra, panties, etc. |
| object_visibility | string | The degree of target visibility in the image, such as fully visible, partially occluded, etc. |
| lighting_conditions | string | The lighting conditions in the image, such as bright, dark, artificial light. |
| background_clarity | string | The clarity of the image background, such as clear or blurry. |
| annotation_quality | int | The accuracy of the image annotations, rated on a scale of 1 to 5. |
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 |
Frequently Asked Questions
- How many images are included in the dataset?
- The lingerie occlusion recognition image dataset contains thousands of images for training and testing.
- What machine learning tasks is this dataset suitable for?
- This dataset is suitable for object detection tasks, especially detecting occlusions in complex scenarios of lingerie products.
- What is the main application scenario for this dataset?
- The main application is in the retail e-commerce field, improving the robustness and recall rate of lingerie product detection models under complex shooting conditions.
- Why choose to use this dataset?
- This dataset is chosen because it focuses on addressing the common occlusion problems of lingerie products in retail environments, providing valuable data for training models in complex scenarios.
- How does this dataset help improve model performance?
- By providing annotated images under complex occlusion conditions, it helps models better recognize and detect lingerie products, thereby improving robustness and recall rates.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Underwear Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/76977c7de67ac664f14d479c2560c143},
urldate={2025-08-28},
keywords={underwear dataset,image occlusion dataset,e-commerce image dataset,retail product recognition},
version={1.0}
}Using this in research? Please cite us.
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