Jeans Occlusion Image Dataset
#object detection #image segmentation #fashion recognition #product detection #image classification
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-09-20
AI Analysis & Value Prop
The retail e-commerce industry faces significant challenges in accurately recognizing clothing items due to occlusions that occur in various contexts, such as partially covered items in images. Existing solutions often struggle with robustness against such occlusions, leading to reduced accuracy in automated recognition systems. This dataset aims to address the specific technical challenges of occluded denim images, providing a diverse set of instances where jeans are obstructed by various elements like upper garments or seating positions. The data is collected using high-resolution cameras in controlled lighting environments, ensuring clarity and detail. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert review to maintain high standards. The dataset is organized in a JPG format with clear labeling for each image's occlusion characteristics.
Dataset Insights
Sample Examples
e3ebc608**.jpg|1147*1743|119.76 KB
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f4ce2269**.png|1944*4680|7.49 MB
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c9f2625d**.jpg|930*2148|153.49 KB
a55e70c5**.jpg|1211*1651|153.15 KB
e1e0cdbc**.jpg|831*2406|148.27 KB
2a37fb76**.jpg|940*2127|131.01 KB
7e0e0ff7**.png|2160*2826|5.52 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_count | int | The number of jeans objects in the image |
| occlusion_level | string | The degree of jeans occlusion in the image, with possible values: no occlusion, partial occlusion, severe occlusion |
| visibility_area | float | The proportion of the visible part of the jeans in the image |
| color | string | The main color of the jeans in the image |
| texture_detail | string | Texture characteristics of the jeans, such as smooth, wrinkled, or faded |
| size_approximation | string | Approximate size estimation of the jeans in the image, such as small, medium, or large |
| environment_context | string | The type of background environment where the image was taken, such as indoor, outdoor, or white backdrop |
| human_presence | boolean | Whether a human body appears in the image |
| brand_logo_visibility | string | The clarity of the brand logo on the jeans, for example: clear, blurry, not visible |
| fit_type | string | The style of the jeans, for example: straight, skinny, flared |
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
- For what image processing tasks is this dataset suitable?
- The Jeans Product Occlusion Recognition Image Dataset is suitable for object detection tasks and can be used to improve product recognition accuracy, especially when dealing with occluded or partially visible products.
- How can the retail industry use this dataset to enhance image recognition capabilities on e-commerce platforms?
- The retail industry can use this dataset to train models, thus enhancing the ability to automatically recognize and classify products on e-commerce platforms and better handle occlusion issues of jeans products in images.
- Does this dataset include annotation information?
- Yes, the Jeans Product Occlusion Recognition Image Dataset includes detailed annotation information to accurately identify the location and occlusion level of products in the images.
- How can the impact of occlusion on recognition accuracy be addressed when using the dataset for model training?
- During model training, specially designed annotations and occlusion samples from the dataset can be used to adjust recognition algorithms, allowing the model to handle product occlusions better and improve overall recognition accuracy.
- Can this dataset be used for real-time retail monitoring systems?
- After training, this dataset can indeed be applied to real-time retail monitoring systems to assist in real-time recognition and management of jeans product inventory and display conditions.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Jeans Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/d50d9c5b35c344e754a891cd1f00b8ce},
urldate={2025-08-28},
keywords={jeans dataset,image occlusion,fashion recognition dataset,retail e-commerce dataset},
version={1.0}
}Using this in research? Please cite us.
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