{"id":"https://openalex.org/W3091580890","doi":"https://doi.org/10.1109/icra40945.2020.9197024","title":"Adversarial Appearance Learning in Augmented Cityscapes for Pedestrian Recognition in Autonomous Driving","display_name":"Adversarial Appearance Learning in Augmented Cityscapes for Pedestrian Recognition in Autonomous Driving","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3091580890","doi":"https://doi.org/10.1109/icra40945.2020.9197024","mag":"3091580890"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9197024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9197024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.13507","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071554545","display_name":"Artem Savkin","orcid":"https://orcid.org/0000-0002-4767-7153"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Artem Savkin","raw_affiliation_strings":["TU Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Munich","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052980190","display_name":"Thomas Lapotre","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thomas Lapotre","raw_affiliation_strings":["TU Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Munich","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022288358","display_name":"Kevin A. Strauss","orcid":"https://orcid.org/0000-0002-6429-8657"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kevin Strauss","raw_affiliation_strings":["TU Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Munich","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010189219","display_name":"Uzair Akbar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uzair Akbar","raw_affiliation_strings":["TU Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Munich","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041092666","display_name":"Federico Tombari","orcid":"https://orcid.org/0000-0001-5598-5212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Federico Tombari","raw_affiliation_strings":["TU Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Munich","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3305","last_page":"3311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7849013805389404},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7213335037231445},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6670305728912354},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6322060823440552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6310799717903137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5183240175247192},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5013391971588135},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47773998975753784},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46180954575538635},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.46006572246551514},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.45058178901672363},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4413068890571594},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4395591616630554},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.43357834219932556},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40497273206710815},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12038728594779968},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.10273587703704834}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7849013805389404},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7213335037231445},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6670305728912354},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6322060823440552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6310799717903137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5183240175247192},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5013391971588135},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47773998975753784},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46180954575538635},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.46006572246551514},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.45058178901672363},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4413068890571594},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4395591616630554},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.43357834219932556},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40497273206710815},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12038728594779968},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.10273587703704834},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra40945.2020.9197024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9197024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2509.13507","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.13507","pdf_url":"https://arxiv.org/pdf/2509.13507","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.13507","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.13507","pdf_url":"https://arxiv.org/pdf/2509.13507","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1945811542","https://openalex.org/W2010625607","https://openalex.org/W2036196300","https://openalex.org/W2083544878","https://openalex.org/W2099471712","https://openalex.org/W2106413791","https://openalex.org/W2108004794","https://openalex.org/W2111187045","https://openalex.org/W2119112357","https://openalex.org/W2146203184","https://openalex.org/W2150066425","https://openalex.org/W2171943915","https://openalex.org/W2340897893","https://openalex.org/W2397830550","https://openalex.org/W2412782625","https://openalex.org/W2431874326","https://openalex.org/W2461677039","https://openalex.org/W2487365028","https://openalex.org/W2576289912","https://openalex.org/W2608461606","https://openalex.org/W2786559811","https://openalex.org/W2876993306","https://openalex.org/W2883068149","https://openalex.org/W2962729993","https://openalex.org/W2962793481","https://openalex.org/W2962808524","https://openalex.org/W2962867954","https://openalex.org/W2962947361","https://openalex.org/W2962970380","https://openalex.org/W2963038612","https://openalex.org/W2963073614","https://openalex.org/W2963150697","https://openalex.org/W2963539305","https://openalex.org/W2963709863","https://openalex.org/W2963800363","https://openalex.org/W2964035707","https://openalex.org/W4240805545","https://openalex.org/W4289129513","https://openalex.org/W4294643831","https://openalex.org/W4295719664","https://openalex.org/W4320013936","https://openalex.org/W6640680105","https://openalex.org/W6712616374","https://openalex.org/W6715287400","https://openalex.org/W6729966448","https://openalex.org/W6745560452","https://openalex.org/W6745935785","https://openalex.org/W6746282794","https://openalex.org/W6746655403","https://openalex.org/W6747400857","https://openalex.org/W6748312029","https://openalex.org/W6753207496","https://openalex.org/W6754259245","https://openalex.org/W7036195979"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4310988119"],"abstract_inverted_index":{"In":[0,30,63],"the":[1,57,70,83,93],"autonomous":[2,15],"driving":[3],"area":[4],"synthetic":[5,26],"data":[6,20,35],"is":[7],"crucial":[8],"for":[9,54,79],"cover":[10],"specific":[11],"traffic":[12,40],"scenarios":[13,41],"which":[14],"vehicle":[16],"must":[17],"handle.":[18],"This":[19],"commonly":[21],"introduces":[22],"domain":[23],"gap":[24],"between":[25],"and":[27,97],"real":[28],"domains.":[29],"this":[31],"paper":[32],"we":[33,72],"deploy":[34],"augmentation":[36,55,67],"to":[37,46,65],"generate":[38],"custom":[39],"with":[42,60],"VRUs":[43],"in":[44],"order":[45,64],"improve":[47,66],"pedestrian":[48],"recognition.":[49],"We":[50,87],"provide":[51],"a":[52,74],"pipeline":[53,71],"of":[56,69,82,95],"Cityscapes":[58],"dataset":[59],"virtual":[61],"pedestrians.":[62],"realism":[68],"reveal":[73],"novel":[75],"generative":[76],"network":[77],"architecture":[78],"adversarial":[80],"learning":[81],"data-set":[84],"lighting":[85],"conditions.":[86],"also":[88],"evaluate":[89],"our":[90],"approach":[91],"on":[92],"tasks":[94],"semantic":[96],"instance":[98],"segmentation.":[99]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
