{"id":"https://openalex.org/W3048520814","doi":"https://doi.org/10.1145/3394171.3413784","title":"LGNN","display_name":"LGNN","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3048520814","doi":"https://doi.org/10.1145/3394171.3413784","mag":"3048520814"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413784","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.05892","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Quan Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Meng","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiakai Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiakai Zhang","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qiang Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Hu","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xuming He","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuming He","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jingyi Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyi Yu","raw_affiliation_strings":["Shanghai Tech University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Tech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":24.4728,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.98969588,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4364","last_page":"4372"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8996999859809875,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8996999859809875,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.808899998664856,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.762499988079071,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5877000093460083},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5286999940872192},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.4584999978542328},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43650001287460327},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4153999984264374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4153999984264374},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4034999907016754},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3977000117301941}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7325000166893005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452999711036682},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5877000093460083},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5286999940872192},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43650001287460327},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3977000117301941},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34130001068115234},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.26109999418258667}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3394171.3413784","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2008.05892","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.05892","pdf_url":"https://arxiv.org/pdf/2008.05892","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:2008.05892","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.05892","pdf_url":"https://arxiv.org/pdf/2008.05892","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W418579443","https://openalex.org/W1498183729","https://openalex.org/W1536680647","https://openalex.org/W1557257626","https://openalex.org/W1964005581","https://openalex.org/W1998447437","https://openalex.org/W2039863764","https://openalex.org/W2100808586","https://openalex.org/W2102605133","https://openalex.org/W2104525659","https://openalex.org/W2108402667","https://openalex.org/W2123042594","https://openalex.org/W2149668583","https://openalex.org/W2156953558","https://openalex.org/W2193145675","https://openalex.org/W2307770531","https://openalex.org/W2328987086","https://openalex.org/W2594098573","https://openalex.org/W2621534427","https://openalex.org/W2737353725","https://openalex.org/W2798943056","https://openalex.org/W2807021761","https://openalex.org/W2886970679","https://openalex.org/W2953809838","https://openalex.org/W2954300568","https://openalex.org/W2955186028","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2981415272","https://openalex.org/W2989604896","https://openalex.org/W2990045899","https://openalex.org/W3012573144","https://openalex.org/W4248766166"],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1,105],"a":[2,18,28,40,53,72,98,106,114],"novel":[3],"real-time":[4,86],"line":[5,36,108],"segment":[6,37,59,109],"detection":[7],"scheme":[8],"called":[9],"Line":[10],"Graph":[11],"Neural":[12],"Network":[13],"(LGNN).":[14],"Existing":[15],"approaches":[16],"require":[17],"computationally":[19],"expensive":[20],"verification":[21],"or":[22],"postprocessing":[23],"step.":[24],"Our":[25],"LGNN":[26,51,83,91],"employs":[27],"deep":[29],"convolutional":[30],"neural":[31,42],"network":[32,43],"(DCNN)":[33],"for":[34,46,57,112],"proposing":[35],"directly,":[38],"with":[39,80],"graph":[41,74],"(GNN)":[44],"module":[45,63],"reasoning":[47],"their":[48],"connectivities.":[49],"Specifically,":[50],"exploits":[52],"new":[54],"quadruplet":[55],"representation":[56],"each":[58],"where":[60],"the":[61,65,81,118],"GNN":[62],"takes":[64],"predicted":[66],"candidates":[67],"as":[68],"vertexes":[69],"and":[70,121],"constructs":[71],"sparse":[73],"to":[75],"enforce":[76],"structural":[77],"context.":[78],"Compared":[79],"state-of-the-art,":[82],"achieves":[84],"near":[85],"performance":[87],"without":[88],"compromising":[89],"accuracy.":[90],"further":[92],"enables":[93],"time-sensitive":[94],"3D":[95,99,115],"applications.":[96],"When":[97],"point":[100],"cloud":[101],"is":[102],"accessible,":[103],"we":[104],"multi-modal":[107],"classification":[110],"technique":[111],"extracting":[113],"wireframe":[116],"of":[117],"environment":[119],"robustly":[120],"efficiently.":[122]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2020-08-18T00:00:00"}