TUD-GV Dataset for Floating Litter Detection (object detection task)

This dataset contains the data used for the publication:

Jia, T., de Vries, R., Kapelan, Z., van Emmerik, T. H., & Taormina, R. (2024). Detecting floating litter in freshwater bodies with semi-supervised deep learning. Water Research, 266, 122405.

This dataset is a subset of the large-scale "TU Delft - Green Village" (TUD-GV), which includes 9,473 RGB images. More details on the TUD-GV dataset can be found at: https://doi.org/10.5281/zenodo.7636124. This subset used in this publication consists of 1,501 images, selected from the full TUD-GV dataset. All floating litter items in this subset have been annotated with bounding boxes. This subset is specifically for detecting floating litter in object detection tasks.

The 1,501 images are stored in the images.zip file, the annotations are stored in the labels_txt.zip file, and the class of the annotation (i.e., litter) is stored in the classes.txt file.

If you use this dataset for a publication, please cite the paper. Here is a BibTeX entry:

@article{jia2024detecting,
title={Detecting floating litter in freshwater bodies with semi-supervised deep learning},
author={Jia, Tianlong and de Vries, Rinze and Kapelan, Zoran and van Emmerik, Tim HM and Taormina, Riccardo},
journal={Water Research},
volume={266},
pages={122405},
year={2024},
publisher={Elsevier}
}