{"id":"https://openalex.org/W4392904439","doi":"https://doi.org/10.1109/icassp48485.2024.10447180","title":"InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization","display_name":"InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392904439","doi":"https://doi.org/10.1109/icassp48485.2024.10447180"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447180","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10447180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100406520","display_name":"Zhimin Zhang","orcid":"https://orcid.org/0000-0002-0531-9112"},"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":"Zhimin Zhang","raw_affiliation_strings":["Peking University,Wangxuan Institute of Computer Technology","Wangxuan Institute of Computer Technology, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Wangxuan Institute of Computer Technology","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035564767","display_name":"Xiang Gao","orcid":"https://orcid.org/0000-0002-3070-9980"},"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":"Xiang Gao","raw_affiliation_strings":["Peking University,Wangxuan Institute of Computer Technology","Wangxuan Institute of Computer Technology, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Wangxuan Institute of Computer Technology","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022039557","display_name":"Wei Hu","orcid":"https://orcid.org/0000-0003-1255-9453"},"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":"Wei Hu","raw_affiliation_strings":["Peking University,Wangxuan Institute of Computer Technology","Wangxuan Institute of Computer Technology, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Wangxuan Institute of Computer Technology","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.6963,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.69243046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"17","issue":null,"first_page":"7420","last_page":"7424"},"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/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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9970999956130981,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.9122105836868286},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7086344957351685},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.684349536895752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5355622172355652},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.49283337593078613},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47976478934288025},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47683802247047424},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47271984815597534},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4645300805568695},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.45890113711357117},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.43290042877197266},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32725203037261963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16184374690055847}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.9122105836868286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7086344957351685},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.684349536895752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5355622172355652},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.49283337593078613},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47976478934288025},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47683802247047424},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47271984815597534},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4645300805568695},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.45890113711357117},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.43290042877197266},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32725203037261963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16184374690055847},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","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},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447180","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10447180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1731081199","https://openalex.org/W1920022804","https://openalex.org/W2594519801","https://openalex.org/W2798328860","https://openalex.org/W2981440248","https://openalex.org/W2983064130","https://openalex.org/W3176726917","https://openalex.org/W3182872328","https://openalex.org/W3196850540","https://openalex.org/W4236965008","https://openalex.org/W4293117528","https://openalex.org/W4297733535","https://openalex.org/W4394671432","https://openalex.org/W6637618735","https://openalex.org/W6683633756","https://openalex.org/W6745537798","https://openalex.org/W6763422710","https://openalex.org/W6767325187","https://openalex.org/W6775269048","https://openalex.org/W6842889262"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W4389574804","https://openalex.org/W3208095355","https://openalex.org/W2371138613","https://openalex.org/W3016928466","https://openalex.org/W2048963458","https://openalex.org/W2177370417","https://openalex.org/W2936725271","https://openalex.org/W43109613","https://openalex.org/W2550979062"],"abstract_inverted_index":{"The":[0,146],"convenience":[1],"of":[2,13,35,42,117,124,138,152],"3D":[3,14,157],"sensors":[4],"has":[5],"led":[6],"to":[7,29,101,112,140],"an":[8],"increase":[9],"in":[10,17,23,31,71],"the":[11,21,32,130,142,150,153],"use":[12],"point":[15,36,43,92,109,118,144],"clouds":[16,93],"various":[18],"applications.":[19],"However,":[20],"differences":[22],"acquisition":[24],"devices":[25],"or":[26],"scenarios":[27,73],"lead":[28],"divergence":[30],"data":[33,77],"distribution":[34],"clouds,":[37,119],"which":[38,56,88],"requires":[39],"good":[40],"generalization":[41,159],"cloud":[44],"representation":[45],"learning":[46,116],"methods.":[47],"While":[48],"most":[49,131],"previous":[50],"methods":[51],"rely":[52],"on":[53,61,156],"domain":[54,63,76,158],"adaptation,":[55],"involves":[57],"fine-tuning":[58],"pre-trained":[59],"models":[60],"target":[62,75],"data,":[64],"this":[65,83],"may":[66,78],"not":[67],"always":[68],"be":[69,79],"feasible":[70],"real-world":[72],"where":[74],"unavailable.":[80],"To":[81],"address":[82],"issue,":[84],"we":[85,120],"propose":[86],"InvariantOODG,":[87],"learns":[89],"invariability":[90],"between":[91],"with":[94],"different":[95],"distributions":[96],"using":[97],"a":[98,122],"two-branch":[99],"network":[100],"extract":[102],"local-to-global":[103],"features":[104],"from":[105],"original":[106],"and":[107,135],"augmented":[108],"clouds.":[110,145],"Specifically,":[111],"enhance":[113],"local":[114,133],"feature":[115],"define":[121],"set":[123],"learnable":[125],"anchor":[126],"points":[127],"that":[128],"locate":[129],"useful":[132],"regions":[134],"two":[136],"types":[137],"transformations":[139],"augment":[141],"input":[143],"experimental":[147],"results":[148],"demonstrate":[149],"effectiveness":[151],"proposed":[154],"model":[155],"benchmarks.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}