{"id":"https://openalex.org/W4385768189","doi":"https://doi.org/10.24963/ijcai.2023/103","title":"ContrastMotion: Self-supervised Scene Motion Learning for Large-Scale LiDAR Point Clouds","display_name":"ContrastMotion: Self-supervised Scene Motion Learning for Large-Scale LiDAR Point Clouds","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385768189","doi":"https://doi.org/10.24963/ijcai.2023/103"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/103","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/103","pdf_url":"https://www.ijcai.org/proceedings/2023/0103.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0103.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102431676","display_name":"Xiangze Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangze Jia","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100656658","display_name":"Hui Zhou","orcid":"https://orcid.org/0000-0002-4422-2911"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hui Zhou","raw_affiliation_strings":["The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005226727","display_name":"Xinge Zhu","orcid":"https://orcid.org/0000-0003-0107-8099"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xinge Zhu","raw_affiliation_strings":["The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038064028","display_name":"Yandong Guo","orcid":"https://orcid.org/0000-0002-4594-8415"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yandong Guo","raw_affiliation_strings":["OPPO Research Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO Research Institute","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100705326","display_name":"Ji Zhang","orcid":"https://orcid.org/0000-0001-7167-6970"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Zhang","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics","Zhejiang Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Zhejiang Lab","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102015139","display_name":"Yuexin Ma","orcid":"https://orcid.org/0000-0001-7237-988X"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuexin Ma","raw_affiliation_strings":["ShanghaiTech University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102015139"],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"929","last_page":"937"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9991000294685364,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9991000294685364,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7832636833190918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7756849527359009},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6488903760910034},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6291379928588867},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5556179285049438},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47375279664993286},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4350190758705139},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4343094825744629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43200698494911194}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832636833190918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7756849527359009},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6488903760910034},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6291379928588867},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5556179285049438},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47375279664993286},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4350190758705139},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4343094825744629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43200698494911194},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2023/103","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/103","pdf_url":"https://www.ijcai.org/proceedings/2023/0103.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/103","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/103","pdf_url":"https://www.ijcai.org/proceedings/2023/0103.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G4040329239","display_name":null,"funder_award_id":"62172372","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5264657428","display_name":null,"funder_award_id":"62206173","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":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385768189.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2286655030","https://openalex.org/W2560609797","https://openalex.org/W2900001365","https://openalex.org/W2962687116","https://openalex.org/W2962771259","https://openalex.org/W2963906250","https://openalex.org/W2968296999","https://openalex.org/W2971686478","https://openalex.org/W2991215750","https://openalex.org/W3034295100","https://openalex.org/W3034321406","https://openalex.org/W3035574168","https://openalex.org/W3081142358","https://openalex.org/W3107422826","https://openalex.org/W3114753236","https://openalex.org/W3116959466","https://openalex.org/W3128818397","https://openalex.org/W3162696321","https://openalex.org/W3166396011","https://openalex.org/W3167095230","https://openalex.org/W3173561529","https://openalex.org/W3175172372","https://openalex.org/W3175582404","https://openalex.org/W3175617025","https://openalex.org/W3178825327","https://openalex.org/W3186678659","https://openalex.org/W3202821542","https://openalex.org/W4206545848","https://openalex.org/W4214793882","https://openalex.org/W4287551944","https://openalex.org/W4290056039","https://openalex.org/W4295312788","https://openalex.org/W4297808394","https://openalex.org/W4303875843","https://openalex.org/W4312374527","https://openalex.org/W4312443676","https://openalex.org/W4312743914","https://openalex.org/W4312825882","https://openalex.org/W4312894406"],"related_works":["https://openalex.org/W4282934273","https://openalex.org/W3119773509","https://openalex.org/W2905271011","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353","https://openalex.org/W3164948662","https://openalex.org/W4289536128"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,27,56],"propose":[4,57,82],"a":[5,76],"novel":[6],"self-supervised":[7,21],"motion":[8,30,135],"estimator":[9],"for":[10,23],"LiDAR-based":[11],"autonomous":[12],"driving":[13],"via":[14,31],"BEV":[15],"representation.":[16],"Different":[17],"from":[18],"usually":[19],"adopted":[20],"strategies":[22],"data-level":[24],"structure":[25],"consistency,":[26],"predict":[28,106],"scene":[29,118,132],"feature-level":[32],"consistency":[33],"between":[34,91],"pillars":[35],"in":[36,52,75],"consecutive":[37],"frames,":[38],"which":[39],"can":[40],"eliminate":[41],"the":[42,63,123],"effect":[43],"caused":[44],"by":[45],"noise":[46],"points":[47],"and":[48,72,114,125,134],"view-changing":[49],"point":[50,92],"clouds":[51],"dynamic":[53],"scenes.":[54],"Specifically,":[55],"Soft":[58],"Discriminative":[59],"Loss":[60],"that":[61,87],"provides":[62],"network":[64],"with":[65],"more":[66],"pseudo-supervised":[67],"signals":[68],"to":[69,96,105],"learn":[70],"discriminative":[71],"robust":[73],"features":[74],"contrastive":[77],"learning":[78],"manner.":[79],"We":[80],"also":[81],"Gated":[83],"Multi-Frame":[84],"Fusion":[85],"block":[86],"learns":[88],"valid":[89],"compensation":[90],"cloud":[93],"frames":[94],"automatically":[95],"enhance":[97],"feature":[98,112],"extraction.":[99],"Finally,":[100],"pillar":[101,107],"association":[102],"is":[103],"proposed":[104],"correspondence":[108],"probabilities":[109],"based":[110],"on":[111,130],"distance,":[113],"whereby":[115],"further":[116],"predicts":[117],"motion.":[119],"Extensive":[120],"experiments":[121],"show":[122],"effectiveness":[124],"superiority":[126],"of":[127],"our":[128],"ContrastMotion":[129],"both":[131],"flow":[133],"prediction":[136],"tasks.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}