Sunglasses Occlusion Image Dataset
#image segmentation #occlusion detection #feature extraction #object detection #image recognition #facial analysis
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-20
AI Analysis & Value Prop
Currently, the retail e-commerce industry faces challenges such as misidentification of products due to occlusions in images, which complicates visual recognition systems. Existing solutions often overlook occlusion scenarios, leading to inaccuracies in product detection. This dataset aims to address specific technical issues related to occlusions caused by hair, shadows, or hands obstructing views of sunglasses, fulfilling the need for improved visual recognition capabilities. The dataset includes images collected from various online retail platforms, ensuring a diverse representation of occlusion types. Quality control measures involve multiple rounds of annotation, consistency checks, and expert reviews, ensuring high accuracy. The data is stored in JPG format, organized in folders categorized by occlusion type.
Dataset Insights
Sample Examples
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| face_count | int | The number of faces appearing in the image |
| sunglasses_presence | boolean | Whether there is a person wearing sunglasses in the image |
| sunglasses_coverage_level | string | The degree of coverage of the face by sunglasses, such as partial coverage, full coverage |
| lighting_conditions | string | The lighting conditions when the image was taken, such as bright, dark, backlit |
| face_orientation | string | The direction of the face in the image, such as front, side, back. |
| skin_tone | string | The skin tone of the person in the image, for example, light, medium, dark. |
| background_complexity | string | The complexity of the image background, such as simple or complex. |
| image_clarity | string | The degree of clarity of the image, such as clear or blurred. |
| eye_visibility | string | The visibility of the eyes in the image, such as fully visible, partially visible, or not visible. |
| object_distance | string | The distance between the face and the camera: near, medium, far. |
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 purpose of the Sunglasses Product Occlusion Detection Image Dataset?
- This dataset is used for developing and testing algorithms for face and occlusion detection under various occlusion conditions, especially in the retail e-commerce sector.
- Which industries can benefit from the Sunglasses Product Occlusion Detection Image Dataset?
- The retail and e-commerce industries can benefit from this dataset by improving the accuracy and intelligence of image recognition and product recommendations for customers.
- How are images in the Sunglasses Product Occlusion Detection Image Dataset labeled?
- Images in the dataset are annotated to identify facial features and various occlusions, supporting the training of object detection models.
- What are the main technologies used with the Sunglasses Product Occlusion Detection Image Dataset?
- The main technologies used include computer vision, deep learning, and their applications in object detection.
- How does the Sunglasses Product Occlusion Detection Image Dataset promote the development of image recognition technology?
- By providing training data under various occlusion conditions, this dataset can enhance facial recognition technology, making it more accurate and robust.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Sunglasses Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/b2dc4ce836fa7a30dfb5a04adeb9f51b},
urldate={2025-08-28},
keywords={sunglasses occlusion dataset,image recognition dataset,occlusion detection,retail e-commerce images},
version={1.0}
}Using this in research? Please cite us.
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