Women's Overcoat Occlusion Image Dataset
#object detection #image segmentation #fashion recognition #e-commerce analysis #visual search
- 15000 records
- 3.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-09-20
AI Analysis & Value Prop
The retail e-commerce sector faces challenges in accurately identifying apparel items due to occlusion caused by background objects and model poses. Current solutions often rely on limited datasets that do not adequately represent diverse occlusion scenarios, leading to poor recognition performance. This dataset aims to address the need for a comprehensive collection of images exhibiting various occlusions to improve object detection and segmentation algorithms. The dataset comprises images collected from online fashion retailers, capturing different poses and occlusions. Quality control measures include multi-round annotations and expert reviews to ensure high accuracy and consistency. Data is stored in JPG format, organized by categories and tagged for easy access.
Dataset Insights
Sample Examples
9638c3d3**.jpg|1280*1000|194.95 KB
d9709a8f**.jpg|1280*2040|377.11 KB
8e3f4d46**.jpg|1280*1970|220.22 KB
e5c26396**.jpg|1280*1706|324.43 KB
07eee7dc**.jpg|1280*2276|264.28 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| coat_color | string | The primary color of the women's coat. |
| model_pose | string | The pose of the model when displaying the coat. |
| background_clutter | string | The level of clutter in the background, such as none, moderate, cluttered, etc. |
| occlusion_level | string | The extent to which the coat is obscured by other objects. |
| attachment_accessories | string | Whether there are accessory attachments on the coat, such as buttons, zippers, belts, etc. |
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
- What is the main purpose of the Ladies' Overcoat Product Occlusion Recognition Image Dataset?
- The main purpose of this dataset is to train and test computer vision algorithms, specifically for object detection tasks related to ladies' overcoats. In scenarios involving occlusions or changes in model poses, algorithms must accurately identify the position and features of the coats.
- How does the Ladies' Overcoat Product Occlusion Recognition Image Dataset assist the retail industry in improving product display?
- The dataset can aid in developing smarter image recognition systems that allow retailers to optimize product displays, improving consumer experience and sales conversion rates even when the products are partially occluded.
- What results can be achieved with algorithms trained on this dataset?
- Algorithms trained on this dataset are expected to more accurately recognize and locate ladies' overcoats, even in cases of occlusions or changes in model poses, thereby enhancing image search functionalities in e-commerce platforms.
- What are the challenging factors in the Ladies' Overcoat Product Occlusion Recognition Image Dataset?
- Challenging factors in this dataset include complex background occlusions, varying model poses, and the appearance of the coats under different conditions, requiring algorithms to have strong generalization capabilities.
- What technologies can be combined with this dataset to enhance retail solutions?
- This dataset can be combined with deep learning, computer vision, and augmented reality technologies to enhance the online shopping experience by offering features like virtual try-ons and personalized recommendations, thereby improving retail solutions.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Women's Overcoat Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/22e9e6faeb60ba1c8db8bde70597d606?dataset_scene_id=9},
urldate={2025-08-28},
keywords={women's overcoat dataset,occlusion detection dataset,fashion image dataset,e-commerce image dataset},
version={1.0}
}Using this in research? Please cite us.
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