Traffic Accident Scene Multi-Target Detection Image Dataset
#target detection #image segmentation #accident analysis #traffic management #intelligent monitoring
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-03-19
AI Analysis & Value Prop
The current transportation sector faces increasingly severe traffic accident issues, and the lack of data leads to inefficient accident analysis and handling. Existing target detection datasets are insufficient in the annotation of vehicles, personnel, and warning lines, limiting the performance enhancement of intelligent transportation systems. This dataset aims to provide high-quality images of traffic accident scenes to support the development of multi-target detection technology and meet the business needs of traffic management and accident analysis. Images in the dataset are captured with high-resolution cameras under different weather and lighting conditions to ensure data diversity and representativeness. Regarding quality control, multiple rounds of annotation and expert review are conducted to ensure the accuracy and consistency of annotation information. Data is stored in JPEG format organized in a folder structure for easy processing and use.
Dataset Insights
Sample Examples
f895e7dc**.jpg|2048*1536|313.42 KB
0f29db0f**.jpg|2560*1920|1.09 MB
68d92207**.jpg|2560*1920|885.71 KB
42918b20**.jpg|1920*1080|458.06 KB
0b3e9908**.jpg|2560*1920|998.62 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| vehicle_count | int | The number of vehicles present in the image. |
| person_count | int | The number of people identifiable in the image. |
| caution_line_presence | boolean | Indicates whether there is a caution line present in the image. |
| weather_condition | string | The weather condition at the time the image was taken, such as sunny, cloudy, or rainy. |
| day_or_night | string | Indicates whether the image was taken during the day or at night. |
| accident_severity | string | The severity of the traffic accident shown in the image, such as minor, moderate, or severe. |
| road_condition | string | The condition of the road shown in the image, such as dry, wet, or icy. |
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 types of images are included in this traffic accident scene multi-object detection image dataset?
- The dataset primarily includes images of traffic accident scenes, featuring various vehicles, pedestrians, road signs, etc.
- How can this dataset be utilized in intelligent transportation systems?
- Researchers can use the dataset for multi-object detection in traffic accident scenes to enhance the intelligence of traffic monitoring and accident recognition.
- What are the advantages of applying this dataset in the traffic industry?
- The dataset provides rich visual data for traffic accident scenes, helping to improve the automation of accident handling and reduce human intervention and misjudgment.
- Is this dataset suitable for training machine learning models?
- Yes, the dataset is suitable for training machine learning models for multi-object detection, especially in intelligent traffic applications.
- What legal regulations should be considered when using this dataset?
- When using the dataset, it is important to comply with data privacy protection regulations to ensure that personal information in the images is not exposed.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Traffic Accident Scene Multi-Target Detection Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/cc026efa4bbf38e22b8a94afda731f27},
urldate={2025-09-15},
keywords={traffic accident dataset, target detection dataset, traffic management, intelligent monitoring},
version={1.0}
}Using this in research? Please cite us.
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