metadata
license: cc-by-nc-4.0
task_categories:
- object-detection
language:
- en
pretty_name: LTDv2
LTDv2: A Large-Scale Long-term Thermal Drift Dataset for Robust Multi-Object Detection in Surveillance
The LTDv2 dataset is designed as a single-scene thermal multi-object detection dataset of over 1 million frames extracted from video clips spanning a period of 8 months. The dataset contains more than 6.8 million annoted bounding boxes of 4 object classes (Person, Bicycle, Motorcycle, Vehicle). Encompasing several seasons, weather conditions and day-night cycles, objects and background exhibits drastic variation in appearance over time. Each image is also paired with meta-data detailing weather related environmental conditions in the area, providing supplementary information to aid the visual domain.
Additional details can be found in the dataset paper.
If you use the LTDv2 dataset, please cite:
@article{LTDv2_dataset,
title={LTDv2: A Large-Scale Long-term Thermal Drift Dataset for Robust Multi-Object Detection in Surveillance},
DOI={10.36227/techrxiv.175339329.95323969/v1},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
author={Parola, Marco and Aakerberg, Andreas and Johansen, Anders S and Nikolov, Ivan A and Cimino, Mario GCA and Nasrollahi, Kamal and Moeslund, Thomas B},
year={2025},
}