C2A Human Detection in Disaster Scenarios Dataset

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The C2A (combined to application) dataset contains a total of 10,215 high-resolution images of 4 disaster scene types (fire/smoke, flood, collapsed building/rubble, and traffic accident) and 5 human posture categories (bending, kneeling, lying down, sitting, and standing upright), with image resolutions ranging from 123×152 to 5184×3456 pixels, and more than 360,000 annotated human instances.

The main sources of the dataset are disaster background and human posture datasets:

1. Disaster background: Derived from the AIDER (Aerial Imagery Dataset for Emergency Response Applications) dataset, it provides real disaster scene images.
2. Human Pose: Derived from the LSP/MPII-MPHB (Multi-Pose Human Body) dataset, providing a wide range of human poses.

This dataset can be used for tasks related to computer vision and machine learning, disaster response and emergency management, drone technology, search and rescue operations, humanitarian assistance and crisis response. It aims to use drone images to improve human detection capabilities in disaster scenes and help develop more powerful and accurate human detection systems for disaster response.