Back to Search Start Over

All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes

Authors :
Gómez, Jose L.
Silva, Manuel
Seoane, Antonio
Borrás, Agnès
Noriega, Mario
Ros, Germán
Iglesias-Guitian, Jose A.
López, Antonio M.
Publication Year :
2023

Abstract

We introduce UrbanSyn, a photorealistic dataset acquired through semi-procedurally generated synthetic urban driving scenarios. Developed using high-quality geometry and materials, UrbanSyn provides pixel-level ground truth, including depth, semantic segmentation, and instance segmentation with object bounding boxes and occlusion degree. It complements GTAV and Synscapes datasets to form what we coin as the 'Three Musketeers'. We demonstrate the value of the Three Musketeers in unsupervised domain adaptation for image semantic segmentation. Results on real-world datasets, Cityscapes, Mapillary Vistas, and BDD100K, establish new benchmarks, largely attributed to UrbanSyn. We make UrbanSyn openly and freely accessible (www.urbansyn.org).<br />Comment: The UrbanSyn Dataset is available in http://urbansyn.org/

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2312.12176
Document Type :
Working Paper