{"id":"https://openalex.org/W4403864453","doi":"https://doi.org/10.1109/qrs-c63300.2024.00140","title":"PreBEV: Leveraging Predictive Flow for Enhanced Bird's-Eye View 3D Dynamic Object Detection","display_name":"PreBEV: Leveraging Predictive Flow for Enhanced Bird's-Eye View 3D Dynamic Object Detection","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4403864453","doi":"https://doi.org/10.1109/qrs-c63300.2024.00140"},"language":"en","primary_location":{"id":"doi:10.1109/qrs-c63300.2024.00140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qrs-c63300.2024.00140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 24th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","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/A5100314193","display_name":"Nan Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Ma","raw_affiliation_strings":["Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100682031","display_name":"Shangyuan Li","orcid":"https://orcid.org/0000-0001-5315-0764"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangyuan Li","raw_affiliation_strings":["Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035402576","display_name":"Yiheng Han","orcid":"https://orcid.org/0000-0002-3986-7555"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiheng Han","raw_affiliation_strings":["Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106416358","display_name":"Mohan Wang","orcid":"https://orcid.org/0009-0001-2154-044X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mohan Wang","raw_affiliation_strings":["Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100314193"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19453266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1062","last_page":"1066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9319999814033508,"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":0.9319999814033508,"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":0.7754610180854797},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6044429540634155},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5388002395629883},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5343424677848816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49331942200660706},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4838322699069977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1748519241809845}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7754610180854797},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6044429540634155},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5388002395629883},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5343424677848816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49331942200660706},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4838322699069977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1748519241809845},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/qrs-c63300.2024.00140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qrs-c63300.2024.00140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 24th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1241786825","display_name":null,"funder_award_id":"2023YFF0615800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3062935211","display_name":null,"funder_award_id":"4222025","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"},{"id":"https://openalex.org/G421140514","display_name":null,"funder_award_id":"62371013,61931012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6490432262","display_name":null,"funder_award_id":"S20210201107","funder_id":"https://openalex.org/F4320309030","funder_display_name":"Small Business Innovation Research"}],"funders":[{"id":"https://openalex.org/F4320309030","display_name":"Small Business Innovation Research","ror":"https://ror.org/015t55b95"},{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W3106834807","https://openalex.org/W3114753236","https://openalex.org/W3173668541","https://openalex.org/W4382450829","https://openalex.org/W4390871716","https://openalex.org/W4390873268","https://openalex.org/W6760782946","https://openalex.org/W6767379092","https://openalex.org/W6781473119","https://openalex.org/W6802311648","https://openalex.org/W6810001583","https://openalex.org/W6810240388","https://openalex.org/W6811079899","https://openalex.org/W6839355098","https://openalex.org/W6853598209"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Recently,":[0],"the":[1,7,13,18,23,43,49,71,77,83,91,99,108,130,148,155,163,168,183,193],"3D":[2],"object":[3,46],"detection":[4,24,172],"problem":[5],"in":[6,58],"autonomous":[8],"driving":[9],"vehicle":[10],"based":[11,123],"on":[12,124,182],"look-around":[14],"camera":[15],"has":[16],"introduced":[17],"spatio-temporal":[19],"consistency":[20],"to":[21,39,75,106,157,192],"improve":[22],"or":[25],"instance":[26],"prediction":[27,169],"performance.":[28],"Dense":[29],"BEV":[30,102,120,196],"spatial":[31],"features":[32],"and":[33,55,81,103,153,166,171],"rich":[34],"temporal":[35],"information":[36,57],"are":[37],"expected":[38],"make":[40],"up":[41],"for":[42],"lack":[44],"of":[45,51,87,101,132,147,151,195],"attention,":[47],"ignoring":[48],"importance":[50],"dynamic":[52,158],"target":[53],"motion":[54,85,149],"position":[56],"future":[59],"image":[60,104],"frames.":[61],"We":[62],"propose":[63],"a":[64,188],"novel":[65],"framework":[66,118],"called":[67],"PreBEV.":[68],"PreBEV":[69,160,179],"introduces":[70],"predictive":[72,125],"stream":[73],"method":[74],"construct":[76],"query":[78],"anchor":[79],"box":[80],"learns":[82],"implicit":[84],"characteristics":[86,150],"sequence":[88],"images":[89],"through":[90],"close":[92],"association":[93],"with":[94],"pixels,":[95],"which":[96,128,186],"effectively":[97,161],"utilizes":[98],"adaptability":[100],"views":[105],"alleviate":[107],"computational":[109],"pressure":[110],"caused":[111],"by":[112,142],"dense":[113],"queries.":[114],"In":[115],"addition,":[116],"this":[117],"proposes":[119],"feature":[121],"fusion":[122,136],"flow":[126],"guidance,":[127],"avoids":[129],"limitations":[131],"traditional":[133],"simple":[134],"time-series":[135],"strategies":[137],"(weighted":[138],"sum,":[139],"series)":[140],"set":[141],"hand,":[143],"makes":[144],"full":[145],"use":[146],"objects":[152],"improves":[154,167],"attention":[156],"objects.":[159],"simplifies":[162],"multi-task":[164],"objective":[165],"stability":[170],"accuracy.":[173],"The":[174],"experimental":[175],"results":[176],"show":[177],"that":[178],"performs":[180],"superior":[181],"NuScenes":[184],"dataset,":[185],"brings":[187],"new":[189],"research":[190],"paradigm":[191],"field":[194],"detection.":[197]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}