The DroneWaste dataset is a public collection of aerial images for developing waste recognition models. Each visible waste instance is annotated with a segmentation mask, a bounding box, and a waste category. The dataset contains 4993 images, 5135 annotations, and 20 waste materials. Each category is mapped to a European Waste Code (EWC) to uniquely identify the waste type. The dataset contains the following artifacts: Images folder: contains the images extracted from all site orthomosaics. Dataset ground truth: JSON file that describes the images and annotations of the dataset using the COCO format. Both segmentation masks and bounding boxes are defined for all annotated waste instances. Information file: general information about the current dataset version. The model training and performance evaluation scripts are available on the GitHub repository: https://github.com/lucamora/dronewaste. The intermediate artifacts, such as original orthomosaics and 3D point clouds, generated during the creation of DroneWaste are available upon request. Acknowledgements This work was funded by the European Union’s Horizon Europe project PERIVALLON – Protecting the EuRopean terrItory from organised enVironmentAl crime through inteLLigent threat detectiON tools, under grant agreement no. 101073952.