{"id":"https://openalex.org/W4408324446","doi":"https://doi.org/10.1109/tpami.2025.3549711","title":"BEVHeight++: Toward Robust Visual Centric 3D Object Detection","display_name":"BEVHeight++: Toward Robust Visual Centric 3D Object Detection","publication_year":2025,"publication_date":"2025-03-11","ids":{"openalex":"https://openalex.org/W4408324446","doi":"https://doi.org/10.1109/tpami.2025.3549711","pmid":"https://pubmed.ncbi.nlm.nih.gov/40067721"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3549711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3549711","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5086082119","display_name":"Lei Yang","orcid":"https://orcid.org/0000-0003-1800-6892"},"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":true,"raw_author_name":"Lei Yang","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081233515","display_name":"Tao Tang","orcid":"https://orcid.org/0000-0001-8526-220X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Tang","raw_affiliation_strings":["Shenzhen Campus, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Campus, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361751","display_name":"Jun Li","orcid":"https://orcid.org/0000-0002-0437-5112"},"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":"Jun Li","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100614598","display_name":"Kun Yuan","orcid":"https://orcid.org/0000-0001-8394-8187"},"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":false,"raw_author_name":"Kun Yuan","raw_affiliation_strings":["Center for Machine Learning Research, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Machine Learning Research, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102738203","display_name":"Kai Wu","orcid":"https://orcid.org/0000-0002-0924-4111"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Wu","raw_affiliation_strings":["Tencent YouTu Lab, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tencent YouTu Lab, Shanghai, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100659434","display_name":"Peng Chen","orcid":"https://orcid.org/0000-0001-6122-0574"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Chen","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035406850","display_name":"Li Wang","orcid":"https://orcid.org/0000-0002-9325-2391"},"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":"Li Wang","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101519939","display_name":"Yi Huang","orcid":"https://orcid.org/0000-0003-1513-8443"},"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":"Yi Huang","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117501290","display_name":"Lei Li","orcid":"https://orcid.org/0000-0001-5650-4513"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390719","display_name":"Xinyu Zhang","orcid":"https://orcid.org/0000-0003-0034-9037"},"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":"Xinyu Zhang","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038563167","display_name":"Kaicheng Yu","orcid":"https://orcid.org/0000-0002-0186-3399"},"institutions":[{"id":"https://openalex.org/I3133055985","display_name":"Westlake University","ror":"https://ror.org/05hfa4n20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133055985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaicheng Yu","raw_affiliation_strings":["Westlake University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Westlake University, Hangzhou, China","institution_ids":["https://openalex.org/I3133055985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5086082119"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":20.1782,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.99486805,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"47","issue":"6","first_page":"5094","last_page":"5111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7561371326446533},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7189594507217407},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6972146034240723},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6492795944213867},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4350326657295227},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.42487427592277527},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.41982612013816833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38022932410240173}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7561371326446533},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7189594507217407},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6972146034240723},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6492795944213867},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4350326657295227},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.42487427592277527},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41982612013816833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38022932410240173}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3549711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3549711","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40067721","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40067721","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6313768182","display_name":null,"funder_award_id":"62273198","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G650202614","display_name":null,"funder_award_id":"52072215","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":80,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2184393491","https://openalex.org/W2194775991","https://openalex.org/W2897529137","https://openalex.org/W2963488291","https://openalex.org/W2966926453","https://openalex.org/W2967324759","https://openalex.org/W2968296999","https://openalex.org/W2981857055","https://openalex.org/W2999947750","https://openalex.org/W3034479628","https://openalex.org/W3035049382","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3087402140","https://openalex.org/W3106834807","https://openalex.org/W3109395584","https://openalex.org/W3148242781","https://openalex.org/W3152771138","https://openalex.org/W3167095230","https://openalex.org/W3169690993","https://openalex.org/W3171032126","https://openalex.org/W3173668541","https://openalex.org/W3176319743","https://openalex.org/W3187011621","https://openalex.org/W3203597819","https://openalex.org/W3204439495","https://openalex.org/W3215100485","https://openalex.org/W4200496373","https://openalex.org/W4200629389","https://openalex.org/W4214558638","https://openalex.org/W4224947594","https://openalex.org/W4225793049","https://openalex.org/W4226305814","https://openalex.org/W4281672996","https://openalex.org/W4285740874","https://openalex.org/W4285813083","https://openalex.org/W4292948926","https://openalex.org/W4311727313","https://openalex.org/W4312273592","https://openalex.org/W4312309370","https://openalex.org/W4312713480","https://openalex.org/W4312842574","https://openalex.org/W4312865155","https://openalex.org/W4312939270","https://openalex.org/W4330338357","https://openalex.org/W4362654659","https://openalex.org/W4363675266","https://openalex.org/W4367146742","https://openalex.org/W4368617569","https://openalex.org/W4380763527","https://openalex.org/W4382450829","https://openalex.org/W4382464460","https://openalex.org/W4382466543","https://openalex.org/W4385312729","https://openalex.org/W4386075696","https://openalex.org/W4386075853","https://openalex.org/W4386076667","https://openalex.org/W4390872833","https://openalex.org/W4390873008","https://openalex.org/W4390874598","https://openalex.org/W4392502315","https://openalex.org/W4399666337","https://openalex.org/W4401163421","https://openalex.org/W4401634204","https://openalex.org/W4402704555","https://openalex.org/W4403841936","https://openalex.org/W4405219754","https://openalex.org/W6686211706","https://openalex.org/W6757817989","https://openalex.org/W6767379092","https://openalex.org/W6799331316","https://openalex.org/W6802311648","https://openalex.org/W6810001583","https://openalex.org/W6811230113","https://openalex.org/W6838873368","https://openalex.org/W6842870094","https://openalex.org/W6845491643","https://openalex.org/W6847281901","https://openalex.org/W6851123386"],"related_works":["https://openalex.org/W2114275278","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W1489511283","https://openalex.org/W2974914859","https://openalex.org/W2026565050","https://openalex.org/W2110244802","https://openalex.org/W2163728705","https://openalex.org/W949345935","https://openalex.org/W2109550041"],"abstract_inverted_index":{"While":[0],"most":[1],"recent":[2],"autonomous":[3],"driving":[4],"system":[5],"focuses":[6],"on":[7,11,45,55,176,191],"developing":[8],"perception":[9,29,116],"methods":[10,42,52,153,167],"ego-vehicle":[12,162],"sensors,":[13],"people":[14],"tend":[15],"to":[16,21,26,91,101,104,109,136],"overlook":[17],"an":[18],"alternative":[19],"approach":[20],"leverage":[22],"intelligent":[23],"roadside":[24,46,145],"cameras":[25],"extend":[27],"the":[28,32,38,57,60,64,68,71,76,99,102,111,161,177,192,206],"ability":[30],"beyond":[31],"visual":[33],"range.":[34],"We":[35],"discover":[36],"that":[37],"state-of-the-art":[39],"vision-centric":[40,152],"detection":[41,142],"perform":[43],"poorly":[44],"cameras.":[47],"This":[48],"is":[49],"because":[50],"these":[51],"mainly":[53],"focus":[54],"recovering":[56],"depth":[58,65,123],"regarding":[59],"camera":[61],"center,":[62],"where":[63],"difference":[66],"between":[67],"car":[69],"and":[70,122,131,173,181,188,199,209],"ground":[72,103],"quickly":[73],"shrinks":[74],"while":[75],"distance":[77],"increases.":[78],"In":[79,95,158],"this":[80,93],"paper,":[81],"we":[82,97,126],"propose":[83],"a":[84,106,128,155],"simple":[85],"yet":[86],"effective":[87],"approach,":[88],"dubbed":[89],"BEVHeight++,":[90],"address":[92],"issue.":[94],"essence,":[96],"regress":[98],"height":[100,121],"achieve":[105,127],"distance-agnostic":[107],"formulation":[108],"ease":[110],"optimization":[112],"process":[113],"of":[114,144,160,170,185],"camera-only":[115],"methods.":[117],"By":[118],"incorporating":[119],"both":[120],"encoding":[124],"techniques,":[125],"more":[129],"accurate":[130],"robust":[132],"projection":[133],"from":[134],"2D":[135],"BEV":[137],"spaces.":[138],"On":[139],"popular":[140],"3D":[141],"benchmarks":[143],"cameras,":[146],"our":[147],"method":[148],"surpasses":[149,165],"all":[150],"previous":[151],"by":[154],"significant":[156],"margin.":[157],"terms":[159],"scenario,":[163],"BEVHeight++":[164],"depth-only":[166],"with":[168,195],"increases":[169],"+2.8%":[171],"NDS":[172,187],"+1.7%":[174],"mAP":[175,190],"nuScenes":[178],"test":[179],"set,":[180],"even":[182],"higher":[183],"gains":[184],"+9.3%":[186],"+8.8%":[189],"nuScenes-C":[193],"benchmark":[194],"object-level":[196],"distortion.":[197],"Consistent":[198],"substantial":[200],"performance":[201],"improvements":[202],"are":[203],"achieved":[204],"across":[205],"KITTI,":[207],"KITTI-360,":[208],"Waymo":[210],"datasets":[211],"as":[212],"well.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":13}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
