{"id":"https://openalex.org/W4383066219","doi":"https://doi.org/10.1109/icra48891.2023.10161214","title":"HFT: Lifting Perspective Representations via Hybrid Feature Transformation for BEV Perception","display_name":"HFT: Lifting Perspective Representations via Hybrid Feature Transformation for BEV Perception","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383066219","doi":"https://doi.org/10.1109/icra48891.2023.10161214"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10161214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10161214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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/A5078816801","display_name":"Jiayu Zou","orcid":"https://orcid.org/0009-0000-3150-4947"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"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/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"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiayu Zou","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences;, School of Artificial Intelligence, University of Chinese Academy of Sciences,Beijing,China","Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences;, School of Artificial Intelligence, University of Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748871","display_name":"Zheng Zhu","orcid":"https://orcid.org/0000-0002-0149-0473"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Zhu","raw_affiliation_strings":["PhiGent Robotics,Beijing,China","PhiGent Robotics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"PhiGent Robotics,Beijing,China","institution_ids":[]},{"raw_affiliation_string":"PhiGent Robotics, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101959834","display_name":"Junjie Huang","orcid":"https://orcid.org/0000-0002-5637-0735"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junjie Huang","raw_affiliation_strings":["PhiGent Robotics,Beijing,China","PhiGent Robotics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"PhiGent Robotics,Beijing,China","institution_ids":[]},{"raw_affiliation_string":"PhiGent Robotics, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032637622","display_name":"Tian Yang","orcid":"https://orcid.org/0000-0001-6185-8957"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian Yang","raw_affiliation_strings":["PhiGent Robotics,Beijing,China","PhiGent Robotics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"PhiGent Robotics,Beijing,China","institution_ids":[]},{"raw_affiliation_string":"PhiGent Robotics, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051049837","display_name":"Guan Huang","orcid":"https://orcid.org/0000-0002-9421-7344"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan Huang","raw_affiliation_strings":["PhiGent Robotics,Beijing,China","PhiGent Robotics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"PhiGent Robotics,Beijing,China","institution_ids":[]},{"raw_affiliation_string":"PhiGent Robotics, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026151620","display_name":"Xingang Wang","orcid":"https://orcid.org/0000-0002-6851-0109"},"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/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/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingang Wang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences;, School of Artificial Intelligence, University of Chinese Academy of Sciences,Beijing,China","Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences;, School of Artificial Intelligence, University of Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5078816801"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":6.6177,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.96098496,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7046","last_page":"7053"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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":0.7658963203430176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.675825834274292},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6382372379302979},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5734439492225647},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5562192797660828},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5135550498962402},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5127916932106018},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.47009679675102234},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.46010980010032654},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.43360692262649536},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37589797377586365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18103134632110596}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7658963203430176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.675825834274292},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6382372379302979},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5734439492225647},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5562192797660828},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5135550498962402},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5127916932106018},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.47009679675102234},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.46010980010032654},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.43360692262649536},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37589797377586365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18103134632110596},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10161214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10161214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2054389289","https://openalex.org/W2117539524","https://openalex.org/W2137097255","https://openalex.org/W2150066425","https://openalex.org/W2468368736","https://openalex.org/W2546938941","https://openalex.org/W2620998106","https://openalex.org/W2768282280","https://openalex.org/W2890003176","https://openalex.org/W2948515602","https://openalex.org/W2955189650","https://openalex.org/W2963083779","https://openalex.org/W2963223517","https://openalex.org/W2963351448","https://openalex.org/W2963438049","https://openalex.org/W2964294967","https://openalex.org/W2970562905","https://openalex.org/W2978854499","https://openalex.org/W2989604896","https://openalex.org/W2991216808","https://openalex.org/W3034669477","https://openalex.org/W3035574168","https://openalex.org/W3100744475","https://openalex.org/W3102343027","https://openalex.org/W3109395584","https://openalex.org/W3117234758","https://openalex.org/W3135793940","https://openalex.org/W3138516171","https://openalex.org/W3154131566","https://openalex.org/W3170300491","https://openalex.org/W3172084025","https://openalex.org/W3178277268","https://openalex.org/W3179351458","https://openalex.org/W3183579734","https://openalex.org/W3185026443","https://openalex.org/W3190338597","https://openalex.org/W3207615232","https://openalex.org/W3207732784","https://openalex.org/W3207937839","https://openalex.org/W3207948259","https://openalex.org/W3215100485","https://openalex.org/W4200247997","https://openalex.org/W4200432946","https://openalex.org/W4214530037","https://openalex.org/W4224947594","https://openalex.org/W4225793049","https://openalex.org/W4226305814","https://openalex.org/W4281255813","https://openalex.org/W4289283268","https://openalex.org/W4312641958","https://openalex.org/W4312894406","https://openalex.org/W4312960790","https://openalex.org/W6638523607","https://openalex.org/W6729383884","https://openalex.org/W6749882464","https://openalex.org/W6756392615","https://openalex.org/W6781473119","https://openalex.org/W6799331316","https://openalex.org/W6802311648","https://openalex.org/W6810001583","https://openalex.org/W6810182555","https://openalex.org/W6811079899","https://openalex.org/W6811230113","https://openalex.org/W6838844109"],"related_works":["https://openalex.org/W4389397071","https://openalex.org/W2023045191","https://openalex.org/W2952839243","https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2353644209","https://openalex.org/W3009154991","https://openalex.org/W2945555514","https://openalex.org/W1967016017","https://openalex.org/W2328889547"],"abstract_inverted_index":{"Restoring":[0],"an":[1],"accurate":[2],"Bird's":[3],"Eye":[4],"View":[5],"(BEV)":[6],"map":[7],"plays":[8],"a":[9,104,108,121],"crucial":[10],"role":[11],"in":[12,85,155,166],"the":[13,50,65,77,86,91,134,151,167,178,186,191],"perception":[14,87,157],"of":[15,21,73,93,153,169],"autonomous":[16],"driving.":[17],"The":[18,57,80,129,210],"existing":[19,202],"works":[20],"lifting":[22],"representations":[23],"from":[24],"frontal":[25],"view":[26],"to":[27,90,114,125,136,140],"BEV":[28,156],"can":[29],"be":[30,213],"classified":[31],"into":[32],"two":[33],"categories,":[34],"i.e.,":[35],"Camera":[36,42],"model-Based":[37],"Feature":[38,44,110],"Transformation":[39,45,111],"(CBFT)":[40],"and":[41,55,96,143,162,188],"model-Free":[43],"(CFFT).":[46],"We":[47,149],"empirically":[48],"analyze":[49],"significant":[51],"differences":[52],"between":[53],"CBFT":[54],"CFFT.":[56],"former":[58],"method":[59,82,181],"lift":[60,115],"perspective":[61,116],"features":[62,145],"based":[63,204],"on":[64,185,190,206],"flat-":[66],"world":[67],"assumption,":[68],"which":[69],"often":[70],"causes":[71],"distortion":[72],"regions":[74,142],"lying":[75],"above":[76],"ground":[78],"plane.":[79],"latter":[81],"is":[83],"limited":[84],"performance":[88],"due":[89],"absence":[92],"geometric":[94],"priors":[95],"time-consuming":[97],"computing.":[98],"In":[99],"this":[100],"paper,":[101],"we":[102,119],"propose":[103],"novel":[105],"framework":[106],"with":[107,146],"Hybrid":[109],"module":[112],"(HFT)":[113],"representations.":[117],"Furthermore,":[118],"design":[120],"mutual":[122],"learning":[123],"scheme":[124],"augment":[126],"hybrid":[127],"transformation.":[128],"deformable":[130],"attention":[131,139],"mechanism":[132],"enables":[133],"model":[135],"pay":[137],"more":[138,147],"relevant":[141],"capture":[144],"semantics.":[148],"illustrate":[150],"effectiveness":[152],"HFT":[154,176,200],"tasks,":[158],"such":[159],"as":[160],"segmentation":[161],"object":[163,208],"detection.":[164,209],"Notably,":[165],"task":[168],"semantic":[170],"segmentation,":[171],"extensive":[172],"experiments":[173],"demonstrate":[174],"that":[175],"outperforms":[177,201],"previous":[179],"state-of-the-art":[180],"by":[182],"relatively":[183],"17.9%":[184],"Argoverse":[187],"22.0%":[189],"KITTI":[192],"3D":[193,207],"Object":[194],"dataset.":[195],"With":[196],"negligible":[197],"computing":[198],"budget,":[199],"image-":[203],"methods":[205],"code":[211],"will":[212],"released":[214],"soon.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}