Sneaker Occlusion Image Dataset
#Object Detection #Image Segmentation #Feature Extraction #Product Recognition #Image Classification #E-commerce Search
- 15000 records
- 0.8G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-18
AI Analysis & Value Prop
In the current retail e-commerce landscape, visual recognition systems face significant challenges due to occlusions affecting product visibility, which can lead to misclassification and poor user experience. Existing datasets often lack diverse occlusion scenarios, limiting the training effectiveness of machine learning models. This dataset aims to address these challenges by providing a comprehensive collection of images where sneakers are obscured by factors such as pant legs, blurred shoe tips, and ground reflections or mud. The data is collected using high-resolution cameras in various retail environments to ensure realistic conditions. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high accuracy. The dataset is organized in JPG format, each image accompanied by metadata in a structured manner.
Dataset Insights
Sample Examples
208278fc**.jpg|2080*961|175.18 KB
68dc8942**.jpg|1224*1632|145.16 KB
0ce52da8**.jpg|1623*1279|564.73 KB
b05a92a7**.jpg|932*1748|249.55 KB
db4193d5**.jpg|1632*1224|352.33 KB
f4a356be**.jpg|900*1600|98.55 KB
43d6c29c**.jpg|1885*1060|302.41 KB
bbe5cbdb**.jpg|1632*1224|177.13 KB
03e2ead5**.png|4368*2030|10.90 MB
6fbf69ce**.jpg|2610*1279|927.07 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| dominant_color | string | The main color of the sneakers in the image, indicated by a specific color name or color code |
| brand_logo_visibility | boolean | Whether the brand logo on the sneakers is clearly visible in the image |
| obstruction_level | integer | The degree of occlusion of the sneakers in the image, ranging from 0 (no occlusion) to 10 (completely occluded) |
| angle_of_view | integer | The viewing angle of the sneakers as shown in the image, such as from the front, side, or top |
| light_condition | string | The lighting conditions when the image was taken, such as bright, cloudy, indoor, outdoor, etc. |
| texture_clarity | boolean | Whether the material texture of the sneakers is clearly distinguishable in the image |
| background_clutter | integer | The level of complexity in the image background, ranging from 0 (simple) to 10 (very complex) |
| shoe_orientation | string | The orientation of sneakers in the image, such as left, right, front, or back. |
| reflection_presence | boolean | Whether there are noticeable reflections in the image, such as those on shiny surfaces. |
| depth_of_field | string | The degree of depth of field in the image, referring to the ratio of foreground and background sharpness, such as shallow or deep depth of field. |
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
- Who is the Sneaker Product Occlusion Recognition Image Dataset suitable for?
- This dataset is suitable for professionals in e-commerce and retail industries, including data scientists, machine learning engineers, and researchers studying occlusion handling techniques.
- What problems can be solved using the Sneaker Product Occlusion Recognition Image Dataset?
- This dataset can help solve the problem of inaccurate recognition due to product occlusion on e-commerce platforms, improving the reliability of product display and customer experience.
- What are the main applications of the Sneaker Product Occlusion Recognition Image Dataset?
- This dataset is mainly used for training and testing object detection models on retail platforms, as well as researching and developing computer vision algorithms that handle product occlusion.
- Why is sneaker product occlusion recognition important for e-commerce?
- In e-commerce, clear and accurate product recognition is crucial for sales. Occlusion recognition can enhance product display quality, reduce misjudgments, and lower return rates.
- How can this dataset be used to improve the performance of object detection models?
- By utilizing the rich occlusion scenes in the dataset, the recognition ability of models for occluded objects can be enhanced, resulting in more robust object detection models for various complex scenarios.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Sneaker Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/6b4d1d0d573cf530a90e7c144209aca3},
urldate={2025-08-28},
keywords={Sneaker Dataset,Image Occlusion Dataset,Retail E-commerce Images,Product Recognition Dataset,Deep Learning for E-commerce},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder