Dress Occlusion Image Dataset
#image classification #object detection #image segmentation #fashion analysis #product recognition #visual search
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-06-05
AI Analysis & Value Prop
The retail e-commerce industry is facing challenges in accurately identifying product features due to occlusions from accessories like bags and props. Existing solutions often fail to account for such occlusions, leading to misidentifications and poor customer experiences. This dataset aims to address these technical issues by providing diverse images of dresses with various occlusions, enabling better training for machine learning models. The data is collected through high-quality photography in controlled environments, ensuring consistent lighting and angles. Quality control measures include multiple rounds of annotation, consistency checks, and expert reviews to maintain high annotation accuracy. The dataset is organized in JPG format, with images stored by occlusion type for easy access.
Dataset Insights
Sample Examples
7b20841d**.jpg|1280*2999|1.81 MB
d9e0e42f**.jpg|1224*1632|279.06 KB
9595ebff**.jpg|1061*1884|196.95 KB
3a4a0560**.jpg|1061*1884|158.35 KB
dc7e9a8f**.jpg|1224*1632|172.54 KB
6397a756**.jpg|1280*2999|1.98 MB
3e03bea1**.jpg|1061*1884|184.95 KB
8d516fa3**.jpg|1280*2972|2.84 MB
e12bd4de**.jpg|1224*1484|167.82 KB
0faf6c7d**.jpg|1212*1267|295.54 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| dress_type | string | The style type of the dress, such as A-line, pencil skirt, etc. |
| color | string | The color of the dress. |
| pattern_type | string | Whether the dress has patterns such as stripes, checks, etc. |
| occlusion_level | string | The degree of occlusion of the dress in the image, such as slight occlusion, partial occlusion, severe occlusion, etc. |
| fabric_type | string | The type of fabric used for the dress, such as cotton, silk, denim, etc. |
| sleeve_length | string | The sleeve length of the dress, such as sleeveless, short-sleeve, long-sleeve, etc. |
| neckline_type | string | The neckline design of the dress, such as V-neck, round neck, etc. |
| dress_length | string | The length of the dress, such as mini, midi, long. |
| accessories_present | boolean | Whether there are any related accessories present in the image, such as belts, necklaces, etc. |
| background_complexity | string | The complexity of the image background, such as simple background, complex background, 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 can the Dress Occlusion Recognition Image Dataset be used for?
- This dataset can be used to train machine learning models to recognize scenarios where dresses in product images are occluded by other objects, thereby improving the quality and effectiveness of product displays on e-commerce platforms.
- Which industries are suitable for using the Dress Occlusion Recognition Image Dataset?
- This dataset is mainly suitable for the retail and e-commerce industries, especially in applications where improving product display effect and reducing product occlusion is essential.
- Why is dress occlusion recognition important in the e-commerce domain?
- In the e-commerce domain, clearly displaying products can enhance user experience and boost sales. Dress occlusion recognition helps automatically detect and resolve issues of product occlusion in images, thereby increasing sales conversion rates.
- How does this dataset help improve the performance of machine learning models?
- By offering high-quality dress occlusion data, this dataset provides a wealth of training samples, helping models better learn and recognize occlusion patterns, thus enhancing accuracy and robustness in object detection.
- What are the advantages of using the Dress Occlusion Recognition Image Dataset?
- The main advantages of using this dataset include improving model detection accuracy, reducing occlusion issues in product images, and enhancing the user experience on e-commerce platforms.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Dress Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/6738144c2caaa81b95fef16ef5ed3f5c?cate=2},
urldate={2025-08-28},
keywords={dress occlusion dataset,image dataset for fashion,retail e-commerce images,fashion product recognition dataset},
version={1.0}
}Using this in research? Please cite us.
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