{"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/blitznet-a-real-time-deep-network-for-scene","title":"BlitzNet: A Real-Time Deep Network for Scene Understanding","arxiv_id":"1708.02813","date":"2017-08-09","proceeding":"ICCV 2017 10","authors":["Nikita Dvornik","Konstantin Shmelkov","Julien Mairal","Cordelia Schmid"],"abstract":"Real-time scene understanding has become crucial in many applications such as\nautonomous driving. In this paper, we propose a deep architecture, called\nBlitzNet, that jointly performs object detection and semantic segmentation in\none forward pass, allowing real-time computations. Besides the computational\ngain of having a single network to perform several tasks, we show that object\ndetection and semantic segmentation benefit from each other in terms of\naccuracy. Experimental results for VOC and COCO datasets show state-of-the-art\nperformance for object detection and segmentation among real time systems.","url_abs":"http://arxiv.org/abs/1708.02813v1","url_pdf":"http://arxiv.org/pdf/1708.02813v1.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":"blitznet-a-real-time-deep-network-for-scene","repo_url":"https://github.com/ShunyuYao/blitznet_instance_segment","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"blitznet-a-real-time-deep-network-for-scene","repo_url":"https://github.com/dvornikita/blitznet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"real-time-object-detection","task_name":"Real-Time Object Detection"},{"task_slug":"real-time-semantic-segmentation","task_name":"Real-Time Semantic Segmentation"},{"task_slug":"scene-understanding","task_name":"Scene Understanding"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/object-detection-on-pascal-voc-2007","task":"Object Detection","dataset":"PASCAL VOC 2007","model":"BlitzNet512 + seg (s8)","rank_in_archive_order":9,"of":30,"metrics":{"MAP":"81.5%"},"uses_additional_data":false},{"leaderboard":"/sota/real-time-object-detection-on-pascal-voc-2007","task":"Real-Time Object Detection","dataset":"PASCAL VOC 2007","model":"BlitzNet512 (s4)","rank_in_archive_order":2,"of":4,"metrics":{"FPS":"24","MAP":"79.1%"},"uses_additional_data":false},{"leaderboard":"/sota/real-time-object-detection-on-pascal-voc-2007","task":"Real-Time Object Detection","dataset":"PASCAL VOC 2007","model":"BlitzNet512 (s8)","rank_in_archive_order":3,"of":4,"metrics":{"FPS":"19.5","MAP":"81.5%"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1708.02813","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}