{"id":"https://openalex.org/W4388505075","doi":"https://doi.org/10.1109/lra.2023.3331290","title":"VRVP: Valuable Region and Valuable Point Anchor-Free 3D Object Detection","display_name":"VRVP: Valuable Region and Valuable Point Anchor-Free 3D Object Detection","publication_year":2023,"publication_date":"2023-11-08","ids":{"openalex":"https://openalex.org/W4388505075","doi":"https://doi.org/10.1109/lra.2023.3331290"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2023.3331290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3331290","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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/A5076430249","display_name":"Pengzhen Deng","orcid":"https://orcid.org/0000-0001-8809-3608"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengzhen Deng","raw_affiliation_strings":["Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210119392","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742878","display_name":"Li Zhou","orcid":"https://orcid.org/0000-0003-2391-0093"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhou","raw_affiliation_strings":["Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210119392","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101979804","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0002-1760-4658"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210119392","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076430249"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210119392","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.8463,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75880376,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"9","issue":"1","first_page":"33","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9969000220298767,"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":0.9965000152587891,"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":0.8437188863754272},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.7224428653717041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7077069878578186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6706670522689819},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5809980630874634},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5601029992103577},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5290621519088745},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5002322196960449},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48954781889915466},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4351547956466675},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4138833284378052},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3956288993358612},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18043643236160278},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11789095401763916}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8437188863754272},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7224428653717041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7077069878578186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6706670522689819},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5809980630874634},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5601029992103577},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5290621519088745},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5002322196960449},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48954781889915466},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4351547956466675},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4138833284378052},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3956288993358612},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18043643236160278},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11789095401763916},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2023.3331290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3331290","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6100000143051147,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2555618208","https://openalex.org/W2607037079","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2951517617","https://openalex.org/W2953433119","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2963400571","https://openalex.org/W2963727135","https://openalex.org/W2968296999","https://openalex.org/W2981949127","https://openalex.org/W2982770724","https://openalex.org/W2989604896","https://openalex.org/W2997814983","https://openalex.org/W2998254148","https://openalex.org/W3003618643","https://openalex.org/W3033591146","https://openalex.org/W3034314779","https://openalex.org/W3034602892","https://openalex.org/W3035346742","https://openalex.org/W3035396860","https://openalex.org/W3036853234","https://openalex.org/W3043237494","https://openalex.org/W3089401811","https://openalex.org/W3113028524","https://openalex.org/W3118341329","https://openalex.org/W3166089996","https://openalex.org/W3167732492","https://openalex.org/W3179888767","https://openalex.org/W3204792207","https://openalex.org/W3205844608","https://openalex.org/W3207921941","https://openalex.org/W4200632008","https://openalex.org/W4214777292","https://openalex.org/W4225532949","https://openalex.org/W4225865900","https://openalex.org/W4293811845","https://openalex.org/W4312934050","https://openalex.org/W4386075590","https://openalex.org/W6739778489","https://openalex.org/W6760424586","https://openalex.org/W6763422710","https://openalex.org/W6765561951","https://openalex.org/W6779564934","https://openalex.org/W6779586474","https://openalex.org/W6781679151","https://openalex.org/W6811378280"],"related_works":["https://openalex.org/W3016928466","https://openalex.org/W4389574804","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W3108295644","https://openalex.org/W1578717197","https://openalex.org/W2626737336","https://openalex.org/W2005998065","https://openalex.org/W1984178488","https://openalex.org/W4292830139"],"abstract_inverted_index":{"3D":[0],"point":[1,30],"cloud":[2,31],"object":[3,32,62,86],"detection":[4,63,160],"is":[5,107],"of":[6,28,121,130],"great":[7],"significance":[8],"in":[9,39,117,174],"autonomous":[10],"driving,":[11],"robotics,":[12],"and":[13,68,80,93,98,113,115,138,168],"related":[14],"fields.":[15],"However,":[16],"the":[17,56,75,78,96,118,122,128,135,151],"current":[18],"algorithms":[19],"fail":[20],"to":[21,73,109],"fully":[22],"consider":[23],"that":[24,150],"positive":[25],"sample":[26],"points":[27,44,51,112],"a":[29,90,102],"exclusively":[33],"reside":[34],"on":[35,133],"its":[36],"surface,":[37],"resulting":[38],"decreased":[40],"accuracy.":[41],"High-quality":[42],"classification":[43,79,99],"are":[45,52],"located":[46],"centrally,":[47],"while":[48,170],"high-quality":[49,85],"regression":[50,81,88,97],"predominantly":[53],"situated":[54],"at":[55],"boundary.":[57],"We":[58,83,126],"propose":[59],"an":[60],"anchor-free":[61],"algorithm":[64,132],"called":[65],"Valuable":[66,69],"Region":[67],"Point":[70],"(VRVP),":[71],"aiming":[72],"address":[74],"inconsistency":[76],"between":[77],"tasks.":[82],"achieve":[84],"size":[87],"through":[89],"classification-based":[91],"approach":[92],"implicitly":[94],"correlate":[95],"branches.":[100],"Furthermore,":[101],"valuable":[103,111],"region":[104],"extraction":[105],"module":[106],"introduced":[108],"select":[110],"regions":[114],"fill":[116],"missing":[119],"features":[120],"object's":[123],"center":[124],"area.":[125],"validate":[127],"effectiveness":[129],"our":[131],"both":[134],"KITTI":[136],"dataset":[137,140],"Waymo":[139],"by":[141,157],"comparing":[142],"it":[143],"with":[144],"state-of-the-art":[145],"algorithms.":[146],"The":[147],"results":[148],"demonstrate":[149],"proposed":[152],"method":[153],"exhibits":[154],"strong":[155],"competitiveness":[156],"significantly":[158],"improving":[159],"accuracy":[161,173],"for":[162],"small":[163],"objects":[164],"such":[165],"as":[166],"pedestrians":[167],"cyclists,":[169],"maintaining":[171],"high":[172],"detecting":[175],"cars.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}
