{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/synscapes-a-photorealistic-synthetic-dataset","title":"Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing","arxiv_id":"1810.08705","date":"2018-10-19","proceeding":null,"authors":["Magnus Wrenninge","Jonas Unger"],"abstract":"We introduce Synscapes -- a synthetic dataset for street scene parsing\ncreated using photorealistic rendering techniques, and show state-of-the-art\nresults for training and validation as well as new types of analysis. We study\nthe behavior of networks trained on real data when performing inference on\nsynthetic data: a key factor in determining the equivalence of simulation\nenvironments. We also compare the behavior of networks trained on synthetic\ndata and evaluated on real-world data. Additionally, by analyzing pre-trained,\nexisting segmentation and detection models, we illustrate how uncorrelated\nimages along with a detailed set of annotations open up new avenues for\nanalysis of computer vision systems, providing fine-grain information about how\na model's performance changes according to factors such as distance, occlusion\nand relative object orientation.","url_abs":"http://arxiv.org/abs/1810.08705v1","url_pdf":"http://arxiv.org/pdf/1810.08705v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"synscapes-a-photorealistic-synthetic-dataset","repo_url":"https://github.com/MartinHahner/FoggySynscapes","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"synscapes-a-photorealistic-synthetic-dataset","repo_url":"https://github.com/MartinHahner88/FoggySynscapes","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"scene-parsing","task_name":"Scene Parsing"},{"task_slug":"street-scene-parsing","task_name":"Street Scene Parsing"}],"methods":[],"datasets_introduced":[{"slug":"synscapes","name":"Synscapes","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1810.08705","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}