{"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/slanted-stixels-representing-san-franciscos","title":"Slanted Stixels: Representing San Francisco's Steepest Streets","arxiv_id":"1707.05397","date":"2017-07-17","proceeding":null,"authors":["Daniel Hernandez-Juarez","Lukas Schneider","Antonio Espinosa","David Vázquez","Antonio M. López","Uwe Franke","Marc Pollefeys","Juan C. Moure"],"abstract":"In this work we present a novel compact scene representation based on Stixels\nthat infers geometric and semantic information. Our approach overcomes the\nprevious rather restrictive geometric assumptions for Stixels by introducing a\nnovel depth model to account for non-flat roads and slanted objects. Both\nsemantic and depth cues are used jointly to infer the scene representation in a\nsound global energy minimization formulation. Furthermore, a novel\napproximation scheme is introduced that uses an extremely efficient\nover-segmentation. In doing so, the computational complexity of the Stixel\ninference algorithm is reduced significantly, achieving real-time computation\ncapabilities with only a slight drop in accuracy. We evaluate the proposed\napproach in terms of semantic and geometric accuracy as well as run-time on\nfour publicly available benchmark datasets. Our approach maintains accuracy on\nflat road scene datasets while improving substantially on a novel non-flat road\ndataset.","url_abs":"http://arxiv.org/abs/1707.05397v1","url_pdf":"http://arxiv.org/pdf/1707.05397v1.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":"slanted-stixels-representing-san-franciscos","repo_url":"https://github.com/dhernandez0/stixels","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1707.05397","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}