{"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/semantic-road-layout-understanding-by","title":"Semantic Road Layout Understanding by Generative Adversarial Inpainting","arxiv_id":"1805.11746","date":"2018-05-29","proceeding":null,"authors":["Lorenzo Berlincioni","Federico Becattini","Leonardo Galteri","Lorenzo Seidenari","Alberto del Bimbo"],"abstract":"Autonomous driving is becoming a reality, yet vehicles still need to rely on\ncomplex sensor fusion to understand the scene they act in. The ability to\ndiscern static environment and dynamic entities provides a comprehension of the\nroad layout that poses constraints to the reasoning process about moving\nobjects. We pursue this through a GAN-based semantic segmentation inpainting\nmodel to remove all dynamic objects from the scene and focus on understanding\nits static components such as streets, sidewalks and buildings. We evaluate\nthis task on the Cityscapes dataset and on a novel synthetically generated\ndataset obtained with the CARLA simulator and specifically designed to\nquantitatively evaluate semantic segmentation inpaintings. We compare our\nmethods with a variety of baselines working both in the RGB and segmentation\ndomains.","url_abs":"http://arxiv.org/abs/1805.11746v2","url_pdf":"http://arxiv.org/pdf/1805.11746v2.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":[],"tasks":[{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"sensor-fusion","task_name":"Sensor Fusion"}],"methods":[{"method_slug":"carla","method_name":"CARLA"},{"method_slug":"entropy-regularization","method_name":"Entropy Regularization"},{"method_slug":"ppo","method_name":"PPO"}],"datasets_introduced":[{"slug":"micc-sri","name":"MICC-SRI","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}