Shorts Occlusion Image Dataset
#image classification #object detection #image recognition #object detection #e-commerce analytics
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-18
AI Analysis & Value Prop
The retail e-commerce industry currently faces challenges in accurately identifying clothing items due to occlusions caused by sitting poses and high-contrast lighting. Existing solutions often struggle with occluded items, leading to significant misclassification and poor customer experiences. This dataset aims to address the specific technical issues of occluded clothing identification in various lighting conditions, thereby improving inventory management and customer satisfaction. The dataset comprises images collected from diverse environments, featuring individuals in sitting poses that obscure parts of their shorts. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high accuracy. The images are stored in JPG format, organized by categories based on occlusion types and lighting conditions.
Dataset Insights
Sample Examples
28ed1ebb**.jpg|948*2108|189.55 KB
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c497107b**.png|2537*2065|3.65 MB
28f7fa5e**.png|2645*2067|2.15 MB
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ae9b1a79**.jpg|1224*1632|179.24 KB
f0ca0f78**.jpg|1182*1199|109.12 KB
8b470dcc**.jpg|1036*1931|132.69 KB
4910d1ba**.jpg|2316*3088|2.77 MB
10c1367e**.jpg|909*874|81.30 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_bounding_box | string | The position and size of the shorts in the image, represented in pixels in the format [x_min, y_min, x_max, y_max]. |
| num_of_objects | int | The number of shorts in the image |
| occlusion_level | string | The degree of occlusion of the shorts in the image, such as no occlusion, partially occluded, fully occluded |
| shorts_color | string | The main color of the shorts in the image |
| shorts_length | string | The length characteristics of the shorts, such as short, knee-length, long |
| material_type | string | The material type of the shorts, such as denim, cotton, polyester |
| pattern_type | string | The pattern type on the shorts, such as solid color, stripes, plaids |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 shorts product occlusion recognition image dataset?
- The shorts product occlusion recognition image dataset is a collection of high-quality images used to identify products occluded by shorts, suitable for e-commerce platform product recognition and recommendation.
- Which industries is the shorts product occlusion recognition image dataset suitable for?
- The dataset is mainly suitable for the retail industry, especially online e-commerce platforms.
- How to use the shorts product occlusion recognition image dataset to improve product recognition?
- With the advanced algorithms of this dataset, e-commerce platforms can more accurately recognize products in occluded situations, enhancing the user's shopping experience.
- What is the data modality of the shorts product occlusion recognition image dataset?
- The data modality of this dataset is images.
- How does the shorts product occlusion recognition image dataset support object detection?
- This dataset provides precisely annotated images for object detection, enabling algorithms to recognize and locate shorts in various occluded scenarios.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Shorts Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/6b392a8e0f973c3a60c17abea9254a32?dataset_scene_id=9},
urldate={2025-08-28},
keywords={shorts occlusion dataset,image recognition for clothing,e-commerce image dataset},
version={1.0}
}Using this in research? Please cite us.
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