{"id":"https://openalex.org/W3089401811","doi":"https://doi.org/10.1109/icra40945.2020.9196556","title":"SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud","display_name":"SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3089401811","doi":"https://doi.org/10.1109/icra40945.2020.9196556","mag":"3089401811"},"language":"en","primary_location":{"id":"doi:10.1109/icra40945.2020.9196556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196556","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":"article","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/A5102758362","display_name":"Hongwei Yi","orcid":"https://orcid.org/0000-0001-8669-2009"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongwei Yi","raw_affiliation_strings":["Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083443210","display_name":"Shaoshuai Shi","orcid":"https://orcid.org/0000-0003-2558-181X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoshuai Shi","raw_affiliation_strings":["The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022382771","display_name":"Mingyu Ding","orcid":"https://orcid.org/0000-0001-6556-8359"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mingyu Ding","raw_affiliation_strings":["The University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101424688","display_name":"Jiankai Sun","orcid":"https://orcid.org/0000-0001-5633-1739"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiankai Sun","raw_affiliation_strings":["The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056328626","display_name":"Kui Xu","orcid":"https://orcid.org/0000-0001-7226-5479"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kui Xu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100621161","display_name":"Hui Zhou","orcid":"https://orcid.org/0000-0002-1689-8738"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Zhou","raw_affiliation_strings":["SenseTime Research"],"affiliations":[{"raw_affiliation_string":"SenseTime Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407596","display_name":"Zhe Wang","orcid":"https://orcid.org/0000-0002-0597-4475"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhe Wang","raw_affiliation_strings":["SenseTime Research"],"affiliations":[{"raw_affiliation_string":"SenseTime Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359817","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0002-6258-3147"},"institutions":[{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["School of EECS, Peking University"],"affiliations":[{"raw_affiliation_string":"School of EECS, Peking University","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115588322","display_name":"Guoping Wang","orcid":"https://orcid.org/0000-0001-7819-0076"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Guoping Wang","raw_affiliation_strings":["School of EECS, Peking University"],"affiliations":[{"raw_affiliation_string":"School of EECS, Peking University","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5102758362"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":4.201,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.95383814,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2274","last_page":"2280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9947999715805054,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.826078474521637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8240145444869995},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7692317962646484},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6458178162574768},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6098979115486145},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.605178713798523},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5441615581512451},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5294691324234009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5269825458526611},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.510658323764801},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4606608748435974},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4519301950931549},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.15902891755104065}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.826078474521637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8240145444869995},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7692317962646484},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6458178162574768},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6098979115486145},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.605178713798523},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5441615581512451},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5294691324234009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5269825458526611},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.510658323764801},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4606608748435974},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4519301950931549},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.15902891755104065},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra40945.2020.9196556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra40945.2020.9196556","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1677182931","https://openalex.org/W2150066425","https://openalex.org/W2468368736","https://openalex.org/W2555618208","https://openalex.org/W2560544142","https://openalex.org/W2560609797","https://openalex.org/W2565639579","https://openalex.org/W2591162375","https://openalex.org/W2605189827","https://openalex.org/W2611946301","https://openalex.org/W2613718673","https://openalex.org/W2768282280","https://openalex.org/W2798965597","https://openalex.org/W2886944874","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2951517617","https://openalex.org/W2954174912","https://openalex.org/W2962807143","https://openalex.org/W2962888833","https://openalex.org/W2963121255","https://openalex.org/W2963150697","https://openalex.org/W2963182550","https://openalex.org/W2963351448","https://openalex.org/W2963400571","https://openalex.org/W2963495494","https://openalex.org/W2963727135","https://openalex.org/W2963809933","https://openalex.org/W2964062501","https://openalex.org/W2968296999","https://openalex.org/W2972211064","https://openalex.org/W3106250896","https://openalex.org/W6620707391","https://openalex.org/W6734334479","https://openalex.org/W6739778489","https://openalex.org/W6746052068","https://openalex.org/W6754156300","https://openalex.org/W6757304942","https://openalex.org/W6763422710","https://openalex.org/W6764117818","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W4287694812","https://openalex.org/W3128716822","https://openalex.org/W3046762217","https://openalex.org/W4399442168","https://openalex.org/W2114282491"],"abstract_inverted_index":{"3D":[0],"vehicle":[1],"detection":[2,155],"based":[3],"on":[4,57,151,159],"point":[5,55,178],"cloud":[6,56,179],"is":[7,39,93,132,147],"a":[8,71,79,128],"challenging":[9],"task":[10],"in":[11,37,42,102,172],"real-world":[12],"applications":[13],"such":[14],"as":[15,180],"autonomous":[16],"driving.":[17],"Despite":[18],"significant":[19],"progress":[20],"has":[21],"been":[22],"made,":[23],"we":[24,77],"observe":[25],"two":[26,87],"aspects":[27],"to":[28,83,95,134,149],"be":[29,67,110],"further":[30],"improved.":[31],"First,":[32],"the":[33,52,85,97,103,137,144,160,165,169],"semantic":[34,90,99],"context":[35,91],"information":[36],"LiDAR":[38],"seldom":[40],"explored":[41],"previous":[43],"works,":[44],"which":[45,64],"may":[46,65],"help":[47],"identify":[48],"ambiguous":[49],"vehicles.":[50],"Second,":[51],"distribution":[53,138],"of":[54,143],"vehicles":[58,124],"varies":[59],"continuously":[60],"with":[61,123,177],"increasing":[62],"depths,":[63,127],"not":[66],"well":[68],"modeled":[69],"by":[70,117],"single":[72],"model.":[73],"In":[74],"this":[75,118],"work,":[76],"propose":[78],"unified":[80],"model":[81,136],"SegVoxelNet":[82],"address":[84],"above":[86],"problems.":[88],"A":[89],"encoder":[92],"proposed":[94,166],"leverage":[96],"free-of-charge":[98],"segmentation":[100],"masks":[101],"bird's":[104],"eye":[105],"view.":[106],"Suspicious":[107],"regions":[108,114],"could":[109],"highlighted":[111],"while":[112],"noisy":[113],"are":[115],"suppressed":[116],"module.":[119],"To":[120],"better":[121],"deal":[122],"at":[125],"different":[126],"novel":[129],"depth-aware":[130,145],"head":[131,146],"designed":[133],"explicitly":[135],"differences":[139],"and":[140,175],"each":[141],"part":[142],"made":[148],"focus":[150],"its":[152],"own":[153],"target":[154],"range.":[156],"Extensive":[157],"experiments":[158],"KITTI":[161],"dataset":[162],"show":[163],"that":[164],"method":[167],"outperforms":[168],"state-of-the-art":[170],"alternatives":[171],"both":[173],"accuracy":[174],"efficiency":[176],"input":[181],"only.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}