{"id":"https://openalex.org/W4388240477","doi":"https://doi.org/10.1109/tip.2023.3328230","title":"Self-Supervised 3D Behavior Representation Learning Based on Homotopic Hyperbolic Embedding","display_name":"Self-Supervised 3D Behavior Representation Learning Based on Homotopic Hyperbolic Embedding","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388240477","doi":"https://doi.org/10.1109/tip.2023.3328230","pmid":"https://pubmed.ncbi.nlm.nih.gov/37917516"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2023.3328230","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3328230","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5058878369","display_name":"Jinghong Chen","orcid":"https://orcid.org/0000-0001-8650-790X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghong Chen","raw_affiliation_strings":["Department of Computer Science and Technology, Xiamen University, Xiamen, China","Shenzhen Research Institute, Xiamen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-8650-790X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]},{"raw_affiliation_string":"Shenzhen Research Institute, Xiamen University, Shenzhen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085949548","display_name":"Zhihao Jin","orcid":"https://orcid.org/0000-0003-0507-0035"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Jin","raw_affiliation_strings":["Department of Computer Science and Technology, Xiamen University, Xiamen, China","Shenzhen Research Institute, Xiamen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]},{"raw_affiliation_string":"Shenzhen Research Institute, Xiamen University, Shenzhen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090796235","display_name":"Qicong Wang","orcid":"https://orcid.org/0000-0001-7324-0433"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qicong Wang","raw_affiliation_strings":["Department of Computer Science and Technology, Xiamen University, Xiamen, China","Shenzhen Research Institute, Xiamen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-7324-0433","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]},{"raw_affiliation_string":"Shenzhen Research Institute, Xiamen University, Shenzhen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108055798","display_name":"Hongying Meng","orcid":"https://orcid.org/0000-0002-8836-1382"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hongying Meng","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Brunel University London, Uxbridge, UK"],"raw_orcid":"https://orcid.org/0000-0002-8836-1382","affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Brunel University London, Uxbridge, UK","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1228,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80687696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"32","issue":null,"first_page":"6061","last_page":"6074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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/T10812","display_name":"Human Pose and Action Recognition","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9714000225067139,"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/mathematics","display_name":"Mathematics","score":0.671940803527832},{"id":"https://openalex.org/keywords/hyperbolic-space","display_name":"Hyperbolic space","score":0.6205962300300598},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5991743803024292},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.5407545566558838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5265066027641296},{"id":"https://openalex.org/keywords/homotopy","display_name":"Homotopy","score":0.5130897760391235},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49463245272636414},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4627862572669983},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.453466534614563},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4514646530151367},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4481481909751892},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4428701400756836},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4158509373664856},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.41356319189071655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.31666284799575806},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3069610595703125},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.15187567472457886},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.12461858987808228}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.671940803527832},{"id":"https://openalex.org/C83677898","wikidata":"https://www.wikidata.org/wiki/Q1878538","display_name":"Hyperbolic space","level":2,"score":0.6205962300300598},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5991743803024292},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.5407545566558838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5265066027641296},{"id":"https://openalex.org/C5961521","wikidata":"https://www.wikidata.org/wiki/Q746083","display_name":"Homotopy","level":2,"score":0.5130897760391235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49463245272636414},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4627862572669983},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.453466534614563},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4514646530151367},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4481481909751892},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4428701400756836},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4158509373664856},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.41356319189071655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31666284799575806},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3069610595703125},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.15187567472457886},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.12461858987808228},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2023.3328230","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3328230","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:37917516","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37917516","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:bura.brunel.ac.uk:2438/27535","is_oa":false,"landing_page_url":"https://bura.brunel.ac.uk/handle/2438/27535","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2575303749","display_name":null,"funder_award_id":"2022J011275","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G3205236612","display_name":null,"funder_award_id":"2023J01003","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"}],"funders":[{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W343636949","https://openalex.org/W2113830516","https://openalex.org/W2171534739","https://openalex.org/W2187089797","https://openalex.org/W2295417718","https://openalex.org/W2313903725","https://openalex.org/W2321533354","https://openalex.org/W2765433083","https://openalex.org/W2785325870","https://openalex.org/W2787919227","https://openalex.org/W2797520557","https://openalex.org/W2948058585","https://openalex.org/W2949805239","https://openalex.org/W2963076818","https://openalex.org/W2963282966","https://openalex.org/W2963826423","https://openalex.org/W2964060161","https://openalex.org/W2964134613","https://openalex.org/W3009561768","https://openalex.org/W3034548564","https://openalex.org/W3035524453","https://openalex.org/W3092424783","https://openalex.org/W3103184573","https://openalex.org/W3104591054","https://openalex.org/W3105195350","https://openalex.org/W3108655343","https://openalex.org/W3156509901","https://openalex.org/W3169413442","https://openalex.org/W3171007011","https://openalex.org/W3174708193","https://openalex.org/W3176780013","https://openalex.org/W3194512065","https://openalex.org/W3203227473","https://openalex.org/W3205106480","https://openalex.org/W3216270236","https://openalex.org/W4200634815","https://openalex.org/W4286695273","https://openalex.org/W4287636287","https://openalex.org/W4294371460","https://openalex.org/W4312312750","https://openalex.org/W4312675926","https://openalex.org/W4382240124","https://openalex.org/W4386071754","https://openalex.org/W4387789756","https://openalex.org/W6739076403","https://openalex.org/W6747899497","https://openalex.org/W6751693566","https://openalex.org/W6774670964","https://openalex.org/W6779997284","https://openalex.org/W6784531446","https://openalex.org/W6795754764","https://openalex.org/W6810265253","https://openalex.org/W6814114727","https://openalex.org/W6838789689","https://openalex.org/W6852353798"],"related_works":["https://openalex.org/W2359617897","https://openalex.org/W3109610583","https://openalex.org/W2908248196","https://openalex.org/W2969227564","https://openalex.org/W2087864780","https://openalex.org/W2560283428","https://openalex.org/W2951706337","https://openalex.org/W2515319207","https://openalex.org/W4308565060","https://openalex.org/W4224292393"],"abstract_inverted_index":{"Behavior":[0],"sequences":[1],"are":[2],"generated":[3],"by":[4,61,187],"a":[5,12,113,169,173,184],"series":[6],"of":[7,73,126,134,142,163,192,212,218,233],"spatio-temporal":[8],"interactions":[9],"and":[10,68,111,148,172,215],"have":[11],"high-dimensional":[13],"nonlinear":[14,124],"manifold":[15,56],"structure.":[16],"Therefore,":[17],"it":[18],"is":[19,79,166,176],"difficult":[20,80],"to":[21,40,81,88,107,121,178,200,221],"learn":[22],"3D":[23],"behavior":[24,127],"representations":[25],"without":[26],"relying":[27],"on":[28,118,146],"supervised":[29,224],"signals.":[30],"To":[31],"this":[32,102],"end,":[33],"self-supervised":[34,52,114],"learning":[35,62,106,115],"methods":[36,53],"can":[37],"be":[38],"used":[39],"explore":[41],"the":[42,47,55,63,70,95,123,132,140,143,157,161,164,180,189,195,209,216,227,231],"rich":[43],"information":[44],"contained":[45],"in":[46,58,156,168,194],"data":[48,98,154],"itself.":[49],"Context-context":[50],"contrastive":[51,105],"construct":[54],"embedded":[57,167],"Euclidean":[59,77],"space":[60,78],"distance":[64],"relationship":[65,96,125],"between":[66,97],"data,":[67],"find":[69],"geometric":[71,190,210],"distribution":[72],"data.":[74],"However,":[75],"traditional":[76],"express":[82],"context":[83],"joint":[84],"features.":[85],"In":[86],"order":[87],"obtain":[89,201],"an":[90],"effective":[91],"global":[92,109],"representation":[93],"from":[94],"under":[99],"unlabeled":[100],"conditions,":[101],"paper":[103],"adopts":[104,131],"compare":[108],"feature,":[110],"proposes":[112],"method":[116,130,207],"based":[117,145],"hyperbolic":[119,170,196,213],"embedding":[120],"mine":[122],"trajectories.":[128],"This":[129],"framework":[133],"discarding":[135],"negative":[136,149],"samples,":[137],"which":[138,229],"overcomes":[139],"shortcomings":[141],"paradigm":[144],"positive":[147],"samples":[150],"that":[151],"pull":[152],"similar":[153],"away":[155],"feature":[158],"space.":[159],"Meanwhile,":[160],"output":[162],"network":[165],"space,":[171,197],"multi-layer":[174],"perceptron":[175],"added":[177],"convert":[179],"entire":[181],"module":[182],"into":[183],"homotopic":[185],"mapping":[186],"using":[188],"properties":[191,211],"operations":[193],"so":[198],"as":[199],"homotopy":[202,219],"invariant":[203],"knowledge.":[204],"The":[205],"proposed":[206],"combines":[208],"manifolds":[214],"equivariance":[217],"groups":[220],"promote":[222],"better":[223],"signals":[225],"for":[226],"network,":[228],"improves":[230],"performance":[232],"unsupervised":[234],"learning.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}