Skincare Product Occlusion Image Dataset
#object detection #image segmentation #product recognition #visual search #image classification
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-13
AI Analysis & Value Prop
The skincare industry is rapidly evolving, with brands like Nivea, Cetaphil, Neutrogena, and La Roche-Posay facing challenges in accurately identifying products in various occluded conditions. Current solutions often fall short in handling occlusions and variations in product presentation. This dataset aims to address the technical issues surrounding product recognition under occlusion, which is crucial for improving visual search functionalities in e-commerce. The dataset comprises images collected from retail environments, featuring products in various occluded states. Data collection involved high-resolution photography under controlled lighting conditions to ensure clarity. Quality control was maintained through multiple rounds of annotation, consistency checks, and expert reviews to ensure a high level of accuracy. The images are stored in JPG format, organized by product categories and occlusion levels for easy access.
Dataset Insights
Sample Examples
7ad18d2f**.jpg|1280*1706|138.41 KB
b6d6929d**.jpg|1280*1706|451.91 KB
250a6416**.jpg|1280*2633|506.70 KB
06cd0e6d**.jpg|1280*1706|188.69 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| product_type | string | The specific type of skincare lotion in the image, such as cream, lotion, etc. |
| occlusion_level | float | The degree to which the skincare lotion is occluded in the image, ranging from 0 to 1. |
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 main purpose of the Skincare Lotion Product Occlusion Recognition Image Dataset?
- The main purpose of this dataset is to enhance the recognition technology of skincare lotion products in the retail industry, especially when products are partially occluded.
- What types of images are included in this dataset?
- This dataset includes images of skincare lotion products with varying degrees of occlusion, suitable for object detection tasks.
- How can this dataset be used to improve product recognition technology?
- The dataset can be used to train object detection models, improving the model's ability to recognize occluded objects.
- What are some common algorithms used for training object detection models with this dataset?
- Common algorithms include YOLO, Faster R-CNN, and SSD, which perform well in handling object detection tasks.
- What are the industry application scenarios for this dataset?
- The dataset is used in the retail industry for automatic recognition and inventory management, and it can also improve the accuracy of shopping applications.
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={Skincare Product Occlusion Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/bb5944ecb02a9a9e05993be79aec73e6?dataset_scene_id=9},
urldate={2025-08-28},
keywords={skincare dataset,occlusion images,product recognition dataset,retail e-commerce images},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder