Grand Traffic Auto (GTA) Dataset: a Collection of Synthetic Images for Vehicle Detection, Segmentation and Counting

The Dataset A synthetic dataset for vehicle detection, segmentation, and counting. It comprises images extracted from the highly photo-realistic video game Grand Theft Auto V developed by Rockstar North. Each image is labeled by the game engine providing pixel-wise masks and bounding boxes localizing vehicle instances.The dataset includes about 10k synthetic images depicting several urban scenarios with various background scenes, lighting, camera positions, traffic densities, and weather conditions. In total, we labeled more than 411,000 vehicles. We provide two annotation files: coco_annotations.json --> JSON file that follows the golden standard MS COCO data format (for more info see https://cocodataset.org/#format-data). All the vehicles are labeled with the COCO category 'car'. It is suitable for vehicle detection and instance segmentation. dot_annotations.csv --> CSV file that contains xy coordinates of the centroids of the vehicles. Dot annotation is commonly used for the visual counting task. Citing our work If you found this dataset useful, please cite the following paper @inproceedings{Ciampi_visapp_2021, doi = {10.5220/0010303401850195}, url = {https://doi.org/10.5220%2F0010303401850195}, year = 2021, publisher = {{SCITEPRESS} - Science and Technology Publications}, author = {Luca Ciampi and Carlos Santiago and Joao Costeira and Claudio Gennaro and Giuseppe Amato}, title = {Domain Adaptation for Traffic Density Estimation}, booktitle = {Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications} } and this Zenodo Dataset @dataset{ciampi_gta_6560038, author={Luca Ciampi and Carlos Santiago and Joao Costeira and Claudio Gennaro and Giuseppe Amato}, title = {{Grand Traffic Auto (GTA) Dataset: a Collection of Synthetic Images for Vehicle Detection, Segmentation and Counting}}, month = may, year = 2022, publisher = {Zenodo}, version = {1.0.0}, doi = {10.5281/zenodo.6560038}, url = {https://doi.org/10.5281/zenodo.6560038} } Contact Information If you would like further information about the dataset or if you experience any issues downloading files, please contact us at [e-mail]