{"id":"https://openalex.org/W4390871811","doi":"https://doi.org/10.1109/iccv51070.2023.00763","title":"MV-DeepSDF: Implicit Modeling with Multi-Sweep Point Clouds for 3D Vehicle Reconstruction in Autonomous Driving","display_name":"MV-DeepSDF: Implicit Modeling with Multi-Sweep Point Clouds for 3D Vehicle Reconstruction in Autonomous Driving","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390871811","doi":"https://doi.org/10.1109/iccv51070.2023.00763"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51070.2023.00763","doi":"https://doi.org/10.1109/iccv51070.2023.00763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.00763","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.16715","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100656716","display_name":"Yibo Liu","orcid":"https://orcid.org/0000-0003-1143-3242","observed_orcids":["https://orcid.org/0000-0003-1143-3242"]},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Yibo Liu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab","York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"York University","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101251620","display_name":"Kelly Zhu","orcid":"https://orcid.org/0009-0002-1533-6167","observed_orcids":["https://orcid.org/0009-0002-1533-6167"]},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Kelly Zhu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab","University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I2250955327"]},{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082901351","display_name":"Guile Wu","orcid":"https://orcid.org/0000-0001-7319-473X","observed_orcids":["https://orcid.org/0000-0001-7319-473X"]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guile Wu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043329874","display_name":"Yuan Ren","orcid":"https://orcid.org/0000-0003-1150-6608","observed_orcids":["https://orcid.org/0000-0003-1150-6608"]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Ren","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005698588","display_name":"Bingbing Liu","orcid":"https://orcid.org/0000-0002-5272-3425","observed_orcids":["https://orcid.org/0000-0002-5272-3425"]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingbing Liu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101810463","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-5159-5954","observed_orcids":["https://orcid.org/0000-0001-5159-5954"]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071093853","display_name":"Jinjun Shan","orcid":"https://orcid.org/0000-0002-4911-6739","observed_orcids":["https://orcid.org/0000-0002-4911-6739"]},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jinjun Shan","raw_affiliation_strings":["York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"York University","institution_ids":["https://openalex.org/I192455969"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1263,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.82724044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"8272","last_page":"8282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10531","display_name":"Advanced Vision and Imaging","score":9.999999747378752e-05,"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/T10036","display_name":"Advanced Neural Network Applications","score":9.999999747378752e-05,"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/signed-distance-function","display_name":"signed distance function","score":0.890999972820282},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.8709999918937683},{"id":"https://openalex.org/keywords/partial-point-clouds","display_name":"partial point clouds","score":0.621999979019165},{"id":"https://openalex.org/keywords/multi-view-consistency","display_name":"multi-view consistency","score":0.7059999704360962}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7367125749588013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7136594653129578},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49591025710105896},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4915965497493744},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.456582248210907},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.45416930317878723},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42665308713912964},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4249190092086792},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4201527535915375},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4126589000225067},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51070.2023.00763","doi":"https://doi.org/10.1109/iccv51070.2023.00763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.00763","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2309.16715","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.16715","pdf_url":"https://arxiv.org/pdf/2309.16715","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2309.16715","doi":"https://doi.org/10.48550/arxiv.2309.16715","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2309.16715","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2309.16715","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.16715","pdf_url":"https://arxiv.org/pdf/2309.16715","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390871811.pdf","grobid_xml":"https://content.openalex.org/works/W4390871811.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1987648924","https://openalex.org/W2049981393","https://openalex.org/W2115579991","https://openalex.org/W2160821342","https://openalex.org/W2559882727","https://openalex.org/W2594519801","https://openalex.org/W2606864979","https://openalex.org/W2613115234","https://openalex.org/W2624503621","https://openalex.org/W2748512037","https://openalex.org/W2784125538","https://openalex.org/W2787885212","https://openalex.org/W2791092480","https://openalex.org/W2806871337","https://openalex.org/W2885317998","https://openalex.org/W2886499109","https://openalex.org/W2904383797","https://openalex.org/W2909750748","https://openalex.org/W2938455051","https://openalex.org/W2962778872","https://openalex.org/W2970947021","https://openalex.org/W3004134294","https://openalex.org/W3012056513","https://openalex.org/W3013987637","https://openalex.org/W3034961469","https://openalex.org/W3035172746","https://openalex.org/W3096093845","https://openalex.org/W3109518641","https://openalex.org/W3154129649","https://openalex.org/W3173522942","https://openalex.org/W3196231425","https://openalex.org/W3203898101","https://openalex.org/W3215589927","https://openalex.org/W3215865305","https://openalex.org/W3216682331","https://openalex.org/W4200150166","https://openalex.org/W4214655709","https://openalex.org/W4226368343","https://openalex.org/W4233857083","https://openalex.org/W4312607395","https://openalex.org/W4312706422","https://openalex.org/W4313151476","https://openalex.org/W4383108193","https://openalex.org/W4386075931","https://openalex.org/W4386212288","https://openalex.org/W4394671432","https://openalex.org/W6687484953","https://openalex.org/W6763422710","https://openalex.org/W6811098618","https://openalex.org/W7133192157"],"related_works":["https://openalex.org/W7162417393","https://openalex.org/W3092618660","https://openalex.org/W3215865305","https://openalex.org/W4413010361","https://openalex.org/W4385482736","https://openalex.org/W3042262679","https://openalex.org/W4226178741","https://openalex.org/W3211710982","https://openalex.org/W4417536982","https://openalex.org/W4312529748"],"abstract_inverted_index":{"Reconstructing":[0],"3D":[1,19,152,183],"vehicles":[2,68],"from":[3,62],"noisy":[4],"and":[5,98,105,132,158,177,197,212],"sparse":[6],"partial":[7],"point":[8,64],"clouds":[9,65],"is":[10,146],"of":[11,149,167,203],"great":[12],"significance":[13],"to":[14,26,34,66,107,127,135,163,199],"autonomous":[15,193],"driving.":[16],"Most":[17],"existing":[18],"reconstruction":[20],"methods":[21,209],"cannot":[22],"be":[23,160],"directly":[24],"applied":[25],"this":[27,43,171],"problem":[28,114],"because":[29],"they":[30,81],"are":[31],"elaborately":[32],"designed":[33],"deal":[35],"with":[36,39],"dense":[37],"inputs":[38],"trivial":[40],"noise.":[41],"In":[42,91,170],"work,":[44],"we":[45,93,122],"propose":[46,106],"a":[47,124,137,164],"novel":[48],"framework,":[49],"dubbed":[50],"MV-DeepSDF,":[51],"which":[52],"estimates":[53],"the":[54,70,101,109,150,155,168,201],"optimal":[55,151],"Signed":[56],"Distance":[57],"Function":[58],"(SDF)":[59],"shape":[60,112,153],"representation":[61],"multi-sweep":[63,96],"reconstruct":[67],"in":[69,88,100,154],"wild.":[71],"Although":[72],"there":[73],"have":[74],"been":[75],"some":[76],"SDF-based":[77],"implicit":[78,110,156],"modeling":[79],"methods,":[80],"only":[82],"focus":[83],"on":[84,190],"single-view-based":[85],"reconstruction,":[86],"resulting":[87],"low":[89],"fidelity.":[90],"contrast,":[92],"first":[94],"analyze":[95],"consistency":[97],"complementarity":[99],"latent":[102,140,144],"feature":[103,118],"space":[104,111],"transform":[108],"estimation":[113],"into":[115],"an":[116,147],"element-to-set":[117],"extraction":[119],"problem.":[120],"Then,":[121],"devise":[123],"new":[125],"architecture":[126],"extract":[128],"individual":[129],"element-level":[130],"representations":[131],"aggregate":[133],"them":[134],"generate":[136],"set-level":[138,143],"predicted":[139],"code.":[141],"This":[142],"code":[145],"expression":[148],"space,":[157],"can":[159],"subsequently":[161],"decoded":[162],"continuous":[165],"SDF":[166],"vehicle.":[169],"way,":[172],"our":[173,204],"approach":[174,205],"learns":[175],"consistent":[176],"complementary":[178],"information":[179],"among":[180],"multi-sweeps":[181],"for":[182],"vehicle":[184],"reconstruction.":[185],"We":[186],"conduct":[187],"thorough":[188],"experiments":[189],"two":[191],"real-world":[192],"driving":[194],"datasets":[195],"(Waymo":[196],"KITTI)":[198],"demonstrate":[200],"superiority":[202],"over":[206],"state-of-the-art":[207],"alternative":[208],"both":[210],"qualitatively":[211],"quantitatively.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-01-16T00:00:00"}
