---
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}
}
```