{"id":"https://openalex.org/W4401417072","doi":"https://doi.org/10.1109/icra57147.2024.10611414","title":"Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object Detection","display_name":"Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object Detection","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401417072","doi":"https://doi.org/10.1109/icra57147.2024.10611414"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5085494517","display_name":"Konyul Park","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Konyul Park","raw_affiliation_strings":["Hanyang University,Department of Artificial Intelligence,Seoul,Korea,04763"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Artificial Intelligence,Seoul,Korea,04763","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081582999","display_name":"Yecheol Kim","orcid":"https://orcid.org/0000-0001-8266-4211"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yecheol Kim","raw_affiliation_strings":["Hanyang University,Department of Electrical Engineering,Seoul,Korea,04763"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Electrical Engineering,Seoul,Korea,04763","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082024481","display_name":"Junho Koh","orcid":"https://orcid.org/0000-0003-2318-9128"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Koh","raw_affiliation_strings":["Hanyang University,Department of Electrical Engineering,Seoul,Korea,04763"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Electrical Engineering,Seoul,Korea,04763","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077887449","display_name":"Byungwoo Park","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byungwoo Park","raw_affiliation_strings":["Hanyang University,Department of Artificial Intelligence,Seoul,Korea,04763"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University,Department of Artificial Intelligence,Seoul,Korea,04763","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102839991","display_name":"Jun Won Choi","orcid":"https://orcid.org/0000-0002-3733-0148"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jun Won Choi","raw_affiliation_strings":["Seoul National University,College of Liberal Studies,Department of Electrical and Computer Engineering,Seoul,Korea,08826"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,College of Liberal Studies,Department of Electrical and Computer Engineering,Seoul,Korea,08826","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5311,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83891162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4259","last_page":"4265"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.998199999332428,"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":0.783539891242981},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6945542097091675},{"id":"https://openalex.org/keywords/pillar","display_name":"Pillar","score":0.6901364922523499},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6155736446380615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5647230744361877},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5266499519348145},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.509255051612854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49100711941719055},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4511250853538513},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45003458857536316},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09394210577011108},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07388126850128174}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.783539891242981},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6945542097091675},{"id":"https://openalex.org/C105289051","wikidata":"https://www.wikidata.org/wiki/Q1930094","display_name":"Pillar","level":2,"score":0.6901364922523499},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6155736446380615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5647230744361877},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5266499519348145},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.509255051612854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49100711941719055},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4511250853538513},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45003458857536316},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09394210577011108},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07388126850128174},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10611414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2752782242","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2963121255","https://openalex.org/W2963351448","https://openalex.org/W2963727135","https://openalex.org/W2968296999","https://openalex.org/W2969987486","https://openalex.org/W3004351857","https://openalex.org/W3034236957","https://openalex.org/W3034314779","https://openalex.org/W3035346742","https://openalex.org/W3035574168","https://openalex.org/W3098325765","https://openalex.org/W3109675406","https://openalex.org/W3167095230","https://openalex.org/W4221167453","https://openalex.org/W4225865900","https://openalex.org/W4281672996","https://openalex.org/W4286562540","https://openalex.org/W4312307873","https://openalex.org/W4312617306","https://openalex.org/W4312707458","https://openalex.org/W4313149358","https://openalex.org/W4386066365","https://openalex.org/W4386075590","https://openalex.org/W4386076253","https://openalex.org/W6739778489","https://openalex.org/W6767379092","https://openalex.org/W6785213549","https://openalex.org/W6838873368","https://openalex.org/W6840443303"],"related_works":["https://openalex.org/W2495348380","https://openalex.org/W604547544","https://openalex.org/W4230293041","https://openalex.org/W2377141674","https://openalex.org/W2352149692","https://openalex.org/W4390351107","https://openalex.org/W2368266917","https://openalex.org/W2359627721","https://openalex.org/W4390520112","https://openalex.org/W2911361278"],"abstract_inverted_index":{"Developing":[0],"high-performance,":[1],"real-time":[2],"architectures":[3],"for":[4,11,26,79],"LiDAR-based":[5],"3D":[6],"object":[7],"detectors":[8],"is":[9],"essential":[10],"the":[12,64,111,162],"successful":[13],"commercialization":[14],"of":[15,67,113],"autonomous":[16],"vehicles.":[17],"Pillar-based":[18],"methods":[19,39,59],"stand":[20],"out":[21],"as":[22,50,97,176],"a":[23,90,183],"practical":[24],"choice":[25],"onboard":[27],"deployment":[28],"due":[29],"to":[30,44,96,109],"their":[31,36],"computational":[32,187],"efficiency.":[33],"However,":[34],"despite":[35],"efficiency,":[37],"these":[38],"can":[40],"sometimes":[41],"underperform":[42],"compared":[43],"alternative":[45],"point":[46,114],"encoding":[47,93],"techniques":[48],"such":[49,175],"Voxel-encoding":[51],"or":[52],"PointNet++.":[53],"We":[54],"argue":[55],"that":[56,166],"current":[57],"pillar-based":[58],"have":[60],"not":[61],"sufficiently":[62],"captured":[63],"fine-grained":[65],"distributions":[66],"LiDAR":[68],"points":[69,128],"within":[70,116,129],"each":[71,117,130],"pillar":[72,82,92,118,131],"structure.":[73],"Consequently,":[74],"there":[75],"exists":[76],"considerable":[77],"room":[78],"improvement":[80],"in":[81,186],"feature":[83],"encoding.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88],"introduce":[89],"novel":[91],"architecture":[94],"referred":[95],"Fine-Grained":[98],"Pillar":[99,155],"Feature":[100],"Encoding":[101],"(FG-PFE).":[102],"FG-PFE":[103,167],"utilizes":[104],"Spatio-Temporal":[105],"Virtual":[106],"(STV)":[107],"grids":[108],"capture":[110],"distribution":[112],"clouds":[115],"across":[119],"vertical,":[120],"temporal,":[121],"and":[122,142,179],"horizontal":[123],"dimensions.":[124],"Through":[125],"STV":[126],"grids,":[127],"are":[132,149],"individually":[133],"encoded":[134,147],"using":[135],"Vertical":[136],"PFE":[137,140,144],"(V-PFE),":[138],"Temporal":[139],"(T-PFE),":[141],"Horizontal":[143],"(H-PFE).":[145],"These":[146],"features":[148],"then":[150],"aggregated":[151],"through":[152],"an":[153],"Attentive":[154],"Aggregation":[156],"method.":[157],"Our":[158],"experiments":[159],"conducted":[160],"on":[161],"nuScenes":[163],"dataset":[164],"demonstrate":[165],"achieves":[168],"significant":[169],"performance":[170],"improvements":[171],"over":[172],"baseline":[173],"models":[174],"PointPillar,":[177],"CenterPoint-Pillar,":[178],"PillarNet,":[180],"with":[181],"only":[182],"minor":[184],"increase":[185],"overhead.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}