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

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

URL: http://arxiv.org/abs/2312.12176v2
Date: Fri, 25 Apr 2025 11:35:12 GMT
Title: All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes
Authors: Jose L. Gómez, Manuel Silva, Antonio Seoane, Agnès Borrás, Mario Noriega, Germán Ros, Jose A. Iglesias-Guitian, Antonio M. López,
Abstract summary: UrbanSyn is a dataset acquired through semi-procedurally generated synthetic urban driving scenarios.<n>It provides pixel-level ground truth, including depth, semantic segmentation, and instance segmentation.<n>We make UrbanSyn openly and freely accessible (www.urbansyn.org)
Score: 6.958641426737163
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
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).

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