{"id":"https://openalex.org/W3201194949","doi":"https://doi.org/10.1145/3467691.3467696","title":"End-to-End Lane Detection: a Key Point Approach","display_name":"End-to-End Lane Detection: a Key Point Approach","publication_year":2021,"publication_date":"2021-04-09","ids":{"openalex":"https://openalex.org/W3201194949","doi":"https://doi.org/10.1145/3467691.3467696","mag":"3201194949"},"language":"en","primary_location":{"id":"doi:10.1145/3467691.3467696","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3467691.3467696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Robot Systems and Applications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111790516","display_name":"Chuan Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuan Lv","raw_affiliation_strings":["Primary Affliation, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Primary Affliation, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101744933","display_name":"Jinglei Tang","orcid":"https://orcid.org/0000-0001-5353-7088"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinglei Tang","raw_affiliation_strings":["Primary Affliation, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Primary Affliation, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022509901","display_name":"Ruoqi Wang","orcid":"https://orcid.org/0000-0003-3244-1153"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruoqi Wang","raw_affiliation_strings":["Primary Affliation, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Primary Affliation, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3079,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4555002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.98089998960495,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9638000130653381,"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":0.7274695634841919},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.7139626145362854},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.6202928423881531},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5789106488227844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5784986019134521},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5734336972236633},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5240374207496643},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5138850212097168},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.49710920453071594},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4826353192329407},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.48077529668807983},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4796717166900635},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45720914006233215},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.43032199144363403},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42344290018081665},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42065027356147766},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4122288227081299},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31081390380859375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17803573608398438},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1296238899230957},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11964598298072815}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7274695634841919},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.7139626145362854},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.6202928423881531},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5789106488227844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5784986019134521},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5734336972236633},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5240374207496643},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5138850212097168},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.49710920453071594},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4826353192329407},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.48077529668807983},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4796717166900635},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45720914006233215},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.43032199144363403},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42344290018081665},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42065027356147766},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4122288227081299},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31081390380859375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17803573608398438},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1296238899230957},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11964598298072815},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3467691.3467696","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3467691.3467696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Robot Systems and Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1829670322","https://openalex.org/W1980026261","https://openalex.org/W1990004830","https://openalex.org/W2039544046","https://openalex.org/W2043539602","https://openalex.org/W2051077519","https://openalex.org/W2080553371","https://openalex.org/W2102049273","https://openalex.org/W2118545852","https://openalex.org/W2146575011","https://openalex.org/W2151362034","https://openalex.org/W2156128637","https://openalex.org/W2277132981","https://openalex.org/W2294873883","https://openalex.org/W2963163009","https://openalex.org/W3102168793","https://openalex.org/W4210957799","https://openalex.org/W6682249972"],"related_works":["https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4323768008","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W3023605104","https://openalex.org/W2383578611","https://openalex.org/W2987583674"],"abstract_inverted_index":{"Nowadays,":[0],"autonomous":[1,22],"driving":[2],"is":[3,12,49,170,237],"becoming":[4],"more":[5,7,45],"and":[6,18,35,44,65,70,207,265],"popular.":[8],"Lane":[9],"line":[10,56,76,94,129,135,148,219,236,245],"detection":[11,26,86,162],"very":[13],"important":[14],"for":[15,164],"trajectory":[16],"planning":[17],"decision":[19],"making":[20],"in":[21,104,145,250],"driving.":[23],"Traditional":[24],"lane":[25,55,75,93,128,134,147,168,176,198,218,235,244],"methods":[27,120],"rely":[28],"on":[29,59,184,256,262],"highly":[30],"defined,":[31],"manual":[32],"feature":[33],"extraction":[34],"heuristic":[36],"methods,":[37],"which":[38],"usually":[39,61],"require":[40],"post-processing":[41],"technology.":[42],"More":[43],"recently,":[46],"the":[47,74,81,85,88,92,98,102,114,123,127,132,139,142,154,185,192,201,208,214,221,225,228,234,242,263],"approach":[48],"modeling":[50],"with":[51],"deep":[52],"learning.":[53],"The":[54,118,172,247],"scheme":[57,100,163],"based":[58],"segmentation":[60,103],"requires":[62],"large":[63],"model":[64,209],"complex":[66],"convolution":[67],"structure":[68],"design,":[69],"it":[71,109,259],"cannot":[72],"perceive":[73],"geometric":[77,229],"features.":[78],"Similar":[79],"to":[80,97,190,212,240],"heat":[82],"map":[83],"scheme,":[84],"of":[87,91,113,116,138,141,167,175,188,194,216,233],"key":[89,165,173],"points":[90,166,174,204],"actually":[95],"belongs":[96],"same":[99,226],"as":[101],"a":[105,160],"certain":[106],"angle,":[107],"but":[108],"only":[110,210],"reduces":[111],"part":[112],"amount":[115],"computation.":[117],"current":[119],"all":[121],"ignore":[122],"data":[124,195],"imbalance":[125,196],"between":[126,197],"categories":[130],"that":[131],"near":[133,155],"occupies":[136],"most":[137],"position":[140],"picture,":[143],"resulting":[144],"far":[146,151],"samples":[149],"are":[150,178,205],"less":[152],"than":[153],"samples.":[156],"In":[157],"this":[158,251],"paper,":[159],"novel":[161],"lines":[169,177],"proposed.":[171],"linearly":[179],"sampled":[180,202],"at":[181,220],"different":[182],"intervals":[183],"longitudinal":[186],"axis":[187],"images":[189],"solve":[191],"problem":[193],"lines.":[199],"Then":[200],"anchor":[203,222],"fixed,":[206],"needs":[211],"predict":[213],"abscissa":[215],"each":[217],"points.":[223],"At":[224],"time,":[227],"constraint":[230],"loss":[231],"function":[232],"put":[238],"forward":[239],"ensure":[241],"correct":[243],"shape.":[246],"method":[248],"presented":[249],"paper":[252],"achieves":[253],"50":[254],"FPS":[255],"embedded":[257],"devices,":[258],"achieved":[260],"SOTA":[261],"Culane":[264],"Tusimple":[266],"datasets.":[267]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}