{"id":"https://openalex.org/W7162104848","doi":"https://doi.org/10.48550/arxiv.2605.22086","title":"GenHAR: Generalizing Cross-domain Human Activity Recognition for Last-mile Delivery","display_name":"GenHAR: Generalizing Cross-domain Human Activity Recognition for Last-mile Delivery","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7162104848","doi":"https://doi.org/10.48550/arxiv.2605.22086"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.22086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22086","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.22086","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136759353","display_name":"Zhiqing Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Zhiqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136798350","display_name":"Zelong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zelong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035962376","display_name":"Xiubin Fan","orcid":"https://orcid.org/0009-0000-1805-0530"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Xiubin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136729512","display_name":"Guang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Guang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136805636","display_name":"Baoshen Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Baoshen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136741328","display_name":"Haotian Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haotian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101459338","display_name":"Tian He","orcid":"https://orcid.org/0000-0002-2107-0732"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100603762","display_name":"Desheng Zhang","orcid":"https://orcid.org/0000-0001-9307-8736"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Desheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9229000210762024,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9229000210762024,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.046300001442432404,"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/T12607","display_name":"Personal Information Management and User Behavior","score":0.002300000051036477,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.9016000032424927},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.6809999942779541},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6693000197410583},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5254999995231628},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4959000051021576},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43790000677108765},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.3614000082015991}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.9016000032424927},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.6809999942779541},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6693000197410583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6656000018119812},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5254999995231628},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4959000051021576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47699999809265137},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4090000092983246},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.3614000082015991},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3573000133037567},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3402999937534332},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C176563091","wikidata":"https://www.wikidata.org/wiki/Q669238","display_name":"Intelligent sensor","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27090001106262207},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.2644999921321869}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.22086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22086","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.22086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22086","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.609828531742096,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Human":[0],"Activity":[1],"Recognition":[2],"(HAR)":[3],"has":[4],"shown":[5],"remarkable":[6],"effectiveness":[7],"in":[8,92,156,175],"various":[9],"applications,":[10],"such":[11],"as":[12],"smart":[13],"healthcare":[14],"and":[15,100,123,158,178],"intelligent":[16],"manufacturing.":[17],"However,":[18],"a":[19,53,130,171],"major":[20],"challenge":[21],"faced":[22],"by":[23,62,135,154,163],"HAR":[24,75,113,140],"is":[25],"the":[26,59,71,83,110,118],"distribution":[27],"shift":[28],"across":[29],"different":[30],"sensor":[31,65,98,105],"data":[32,81,99],"domains,":[33],"which":[34],"often":[35],"leads":[36],"to":[37,57,69,108],"decreased":[38],"performance":[39],"when":[40],"deployed":[41],"for":[42],"real-world":[43,143],"applications.":[44],"To":[45],"address":[46],"this":[47,49],"issue,":[48],"paper":[50],"introduces":[51],"GenHAR,":[52],"novel":[54],"framework":[55],"designed":[56],"mitigate":[58],"domain":[60],"gap":[61],"learning":[63],"domain-invariant":[64],"representations.":[66],"GenHAR":[67,90,96,116,134,150,169],"aims":[68],"enhance":[70],"generalization":[72],"capabilities":[73],"of":[74,89,112,133],"on":[76,142],"target":[77],"domains":[78],"purely":[79],"with":[80,138],"from":[82],"source":[84],"domain.":[85],"The":[86],"key":[87],"novelty":[88],"lies":[91],"two":[93],"aspects.":[94],"Firstly,":[95],"tokenizes":[97],"learns":[101],"correlations":[102],"among":[103],"frequency":[104],"channel":[106],"dimensions":[107],"improve":[109],"robustness":[111],"models.":[114],"Secondly,":[115],"improves":[117],"efficiency":[119],"via":[120],"selective":[121],"masking":[122],"an":[124],"efficient":[125],"attention":[126],"mechanism.":[127],"We":[128,185],"conduct":[129],"systematic":[131],"analysis":[132],"comparing":[136],"it":[137],"state-of-the-art":[139,152],"methods":[141,153],"human":[144],"activity":[145],"datasets.":[146],"Results":[147],"show":[148],"that":[149],"outperforms":[151],"9.97%":[155],"accuracy,":[157],"reduces":[159],"Floating":[160],"Point":[161],"Operations":[162],"6.4":[164],"times.":[165],"Moreover,":[166],"we":[167],"deploy":[168],"at":[170],"leading":[172],"logistics":[173],"company":[174],"4":[176],"cities,":[177],"have":[179],"detected":[180],"2.15":[181],"billion":[182],"real-time":[183],"activities.":[184],"release":[186],"our":[187],"code":[188],"at:":[189],"https://github.com/Sensor-FoundationModel/GenHAR.":[190]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-23T00:00:00"}
