Datasets:
| license: mit | |
| task_categories: | |
| - object-detection | |
| tags: | |
| - robotics | |
| - uav | |
| - continual-learning | |
| # UAV-IndoorCL | |
| This repository contains the dataset presented in the paper [Learning on the Fly: Replay-Based Continual Object Perception for Indoor Drones](https://huggingface.co/papers/2602.13440). | |
| [**Project Page**](https://spacetime-vision-robotics-laboratory.github.io/learning-on-the-fly-cl) | [**GitHub**](https://github.com/SpaceTime-Vision-Robotics-Laboratory/learning-on-the-fly-cl) | |
| ## Dataset Summary | |
| UAV-IndoorCL is an indoor video dataset consisting of 14,400 frames capturing inter-drone and ground vehicle footage. It was specifically designed to support and benchmark Class-Incremental Learning (CIL) research for resource-constrained aerial platforms. The frames were annotated via a semi-automatic workflow with high labeling agreement and final manual verification, ensuring temporal coherence across sequences. | |
| ## Citation | |
| If you use this dataset in your research, please cite the following paper: | |
| ```bibtex | |
| @article{nae2026learningflyreplaybasedcontinual, | |
| title = {Learning on the Fly: Replay-Based Continual Object Perception for Indoor Drones}, | |
| author = {Nae, Sebastian-Ion and Barbu, Mihai-Eugen and Mocanu, Sebastian and Leordeanu, Marius}, | |
| journal = {arXiv preprint arXiv:2602.13440}, | |
| year = {2026} | |
| } | |
| ``` |