Update README.md

README.md

@@ -1,3 +1,25 @@
----
-license: cc-by-nc-4.0
----
+---
+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](https://www.techrxiv.org/users/942755/articles/1313175-ltdv2-a-large-scale-long-term-thermal-drift-dataset-for-robust-multi-object-detection-in-surveillance).
+
+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},
+}
+```