{"id":"https://openalex.org/W4392693949","doi":"https://doi.org/10.1109/tvt.2024.3372940","title":"CFPC: The Curbed Fake Point Collector to Pseudo-LiDAR-Based 3D Object Detection for Autonomous Vehicles","display_name":"CFPC: The Curbed Fake Point Collector to Pseudo-LiDAR-Based 3D Object Detection for Autonomous Vehicles","publication_year":2024,"publication_date":"2024-03-12","ids":{"openalex":"https://openalex.org/W4392693949","doi":"https://doi.org/10.1109/tvt.2024.3372940"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2024.3372940","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3372940","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Transactions on Vehicular Technology","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/A5087225784","display_name":"Honghao Gao","orcid":"https://orcid.org/0000-0001-6861-9684"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Honghao Gao","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072350518","display_name":"Jie Shao","orcid":"https://orcid.org/0000-0003-2615-1555"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Shao","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074431197","display_name":"Muddesar Iqbal","orcid":"https://orcid.org/0000-0002-8438-6726"},"institutions":[{"id":"https://openalex.org/I142024983","display_name":"Prince Sultan University","ror":"https://ror.org/053mqrf26","country_code":"SA","type":"education","lineage":["https://openalex.org/I142024983"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Muddesar Iqbal","raw_affiliation_strings":["Renewable Energy Lab, College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Renewable Energy Lab, College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I142024983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423485","display_name":"Ye Wang","orcid":"https://orcid.org/0000-0003-1454-2161"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Wang","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040559321","display_name":"Zhengzhe Xiang","orcid":"https://orcid.org/0000-0003-1133-5722"},"institutions":[{"id":"https://openalex.org/I4400573310","display_name":"Hangzhou City University","ror":"https://ror.org/01wck0s05","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573310"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengzhe Xiang","raw_affiliation_strings":["School of Computer and Computational Science, Hangzhou City University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Computational Science, Hangzhou City University, Hangzhou, China","institution_ids":["https://openalex.org/I4400573310"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5087225784"],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":7.4892,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.98061486,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"74","issue":"2","first_page":"1922","last_page":"1934"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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":0.9977999925613403,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9728999733924866,"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":0.9623000025749207,"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/lidar","display_name":"Lidar","score":0.846926212310791},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6832376718521118},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5499075651168823},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5419240593910217},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5286387205123901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43945932388305664},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3877129852771759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3557189404964447},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19790172576904297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.12113812565803528},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08058619499206543}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.846926212310791},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6832376718521118},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5499075651168823},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5419240593910217},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5286387205123901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43945932388305664},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3877129852771759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3557189404964447},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19790172576904297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.12113812565803528},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08058619499206543},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2024.3372940","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3372940","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6181968682","display_name":null,"funder_award_id":"92367103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2509070647","https://openalex.org/W2555618208","https://openalex.org/W2951517617","https://openalex.org/W2954174912","https://openalex.org/W2963400571","https://openalex.org/W2964062501","https://openalex.org/W2968296999","https://openalex.org/W2988715931","https://openalex.org/W2998633559","https://openalex.org/W3005974859","https://openalex.org/W3012494314","https://openalex.org/W3015248322","https://openalex.org/W3034494113","https://openalex.org/W3034681945","https://openalex.org/W3035346742","https://openalex.org/W3080980548","https://openalex.org/W3118341329","https://openalex.org/W3175720495","https://openalex.org/W3188046901","https://openalex.org/W3201719054","https://openalex.org/W3202229469","https://openalex.org/W3204415296","https://openalex.org/W3206826736","https://openalex.org/W3216015562","https://openalex.org/W3217335336","https://openalex.org/W4200629389","https://openalex.org/W4200632008","https://openalex.org/W4205940831","https://openalex.org/W4214777292","https://openalex.org/W4226098442","https://openalex.org/W4226439325","https://openalex.org/W4312294656","https://openalex.org/W4312437143","https://openalex.org/W4312546175","https://openalex.org/W4312596674","https://openalex.org/W4312713480","https://openalex.org/W4312934050","https://openalex.org/W4313059105","https://openalex.org/W4313149358","https://openalex.org/W4318833281","https://openalex.org/W4319299723","https://openalex.org/W4385835750","https://openalex.org/W4386065523","https://openalex.org/W4386065883","https://openalex.org/W4386075636","https://openalex.org/W4386076370","https://openalex.org/W4386083121","https://openalex.org/W4389352378","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6800161232","https://openalex.org/W6803556390","https://openalex.org/W6810249204","https://openalex.org/W6839446344"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W2351984678","https://openalex.org/W2140032575","https://openalex.org/W2011860471","https://openalex.org/W2012196540","https://openalex.org/W3011451421","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"3D":[0,31,103],"object":[1,32,104],"detection":[2,33,51,105],"in":[3,23,26,53,202,288,292],"autonomous":[4,16,27,54,107],"driving":[5,28,55],"systems":[6],"perceives":[7],"the":[8,13,20,42,50,65,92,116,122,127,133,144,155,198,223,242,252,259,273,279,286,293],"surrounding":[9],"environment":[10],"and":[11,182,258,297],"is":[12,99,176,229,270,283],"foundation":[14],"for":[15,106,110],"driving.":[17],"Due":[18],"to":[19,36,63,71,101,137,161,208,255,262,285],"sparsity":[21,47],"inherent":[22],"point":[24,45,58,87,159,185,194,224],"clouds":[25,59,160],"scenarios,":[29],"LiDAR-based":[30],"often":[34],"fails":[35],"distinguish":[37],"distant":[38,73],"objects":[39],"effectively.":[40],"Addressing":[41],"issue":[43],"of":[44,67,143,147,157,200,244,251,267,275,295],"cloud":[46,195,225],"will":[48],"enhance":[49,64],"range":[52],"scenarios.":[56],"Pseudo":[57],"have":[60],"been":[61],"used":[62],"ability":[66],"deep":[68,134],"learning":[69,135],"models":[70],"detect":[72],"points.":[74,140],"However,":[75],"this":[76,82],"approach":[77,131,269],"has":[78],"several":[79],"shortcomings.":[80],"In":[81],"paper,":[83],"a":[84,162],"curbed":[85],"fake":[86],"collector":[88],"(CFPC),":[89],"which":[90,228],"addresses":[91],"three":[93],"issues":[94],"caused":[95],"by":[96,169,272],"pseudo":[97,193],"points,":[98,148],"proposed":[100],"support":[102],"vehicles.":[108],"First,":[109],"noise":[111,139],"points":[112,201],"with":[113,172,206],"inaccurate":[114],"coordinates,":[115],"dead":[117],"pixel":[118],"checker":[119],"(DPC)":[120],"calculates":[121],"depth":[123],"map":[124],"gradient":[125],"using":[126,226],"Sobel":[128],"operator.":[129],"This":[130,175,187],"enables":[132],"model":[136],"identify":[138],"Second,":[141],"because":[142],"excessive":[145],"quantity":[146],"sparse":[149],"prioritized":[150],"local":[151,203],"sampling":[152,181],"(SPLS)":[153],"reduces":[154],"number":[156],"input":[158],"lightweight":[163],"level":[164],"that":[165,232],"can":[166],"be":[167],"accommodated":[168],"computing":[170],"devices":[171],"limited":[173],"memory.":[174],"achieved":[177],"through":[178],"grid-based":[179],"random":[180],"real-point-prioritized":[183],"farthest":[184],"sampling.":[186],"module":[188],"effectively":[189],"samples":[190],"an":[191,230],"appropriate":[192],"based":[196],"on":[197,278],"density":[199],"space.":[204],"Third,":[205],"respect":[207],"interference":[209],"among":[210],"channels,":[211],"channel":[212],"mask":[213],"set":[214],"abstraction":[215],"(CMSA)":[216],"isolates":[217],"channels":[218,234,254],"describing":[219],"different":[220],"information":[221,257],"within":[222],"GroupMLP,":[227],"MLP":[231],"separates":[233],"into":[235],"their":[236],"respective":[237],"groups.":[238],"Group":[239],"separation":[240],"facilitates":[241],"extraction":[243],"features":[245],"without":[246],"mutual":[247],"influence,":[248],"allocating":[249],"half":[250,261],"output":[253],"color":[256],"other":[260],"geometric":[263],"information.":[264],"The":[265],"effectiveness":[266],"our":[268],"demonstrated":[271],"results":[274],"experiments":[276],"conducted":[277],"KITTI":[280],"dataset.":[281],"It":[282],"superior":[284],"baseline":[287],"most":[289],"situations,":[290],"particularly":[291],"categories":[294],"cars":[296],"riders.":[298]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":9}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
