{"id":"https://openalex.org/W7140163933","doi":"https://doi.org/10.48550/arxiv.2603.21583","title":"HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling","display_name":"HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140163933","doi":"https://doi.org/10.48550/arxiv.2603.21583"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21583","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21583","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21583","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Li, Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Mei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhou, Huayi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Huayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Huang, Suizhi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Suizhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lu, Yuxiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ding, Yue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Lu, Hongtao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Hongtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5353999733924866,"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":0.5353999733924866,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.08100000023841858,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10531","display_name":"Advanced Vision and Imaging","score":0.06030000001192093,"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/rotation","display_name":"Rotation (mathematics)","score":0.6690000295639038},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5234000086784363},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49869999289512634},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4115999937057495},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3959999978542328},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.3939000070095062},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.3400000035762787},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.3386000096797943}],"concepts":[{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.6690000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6338000297546387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6236000061035156},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5234000086784363},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47450000047683716},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.31949999928474426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3190000057220459},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C60316415","wikidata":"https://www.wikidata.org/wiki/Q6664520","display_name":"Local regression","level":4,"score":0.25609999895095825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21583","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21583","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21583","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21583","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7019957900047302,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Regressing":[0],"3D":[1],"rotations":[2],"of":[3,34,63,194],"objects":[4],"from":[5,82,119,159],"2D":[6,44,65],"images":[7,66,158],"is":[8,67],"a":[9,60,104,144],"crucial":[10],"yet":[11],"challenging":[12],"task,":[13],"with":[14,136],"broad":[15],"applications":[16],"in":[17,188],"autonomous":[18],"driving,":[19],"virtual":[20],"reality,":[21],"and":[22,94,128,175,184,199],"robotic":[23],"control.":[24],"Existing":[25],"rotation":[26,56,78,153],"regression":[27,57],"models":[28],"often":[29],"rely":[30],"on":[31,115,173],"large":[32],"amounts":[33],"labeled":[35,64],"data":[36,147],"for":[37,152],"training":[38],"or":[39,50],"require":[40],"additional":[41],"information":[42],"beyond":[43],"images,":[45],"such":[46],"as":[47],"point":[48],"clouds":[49],"CAD":[51],"models.":[52],"Therefore,":[53],"exploring":[54],"semi-supervised":[55,75,185],"using":[58],"only":[59],"limited":[61],"number":[62],"highly":[68],"valuable.":[69],"While":[70],"recent":[71],"work":[72],"FisherMatch":[73],"introduces":[74],"learning":[76,107,197],"to":[77,89,121,132,162],"regression,":[79],"it":[80],"suffers":[81],"rigid":[83],"entropy-based":[84],"pseudo-label":[85],"filtering":[86,135],"that":[87,109,178],"fails":[88],"effectively":[90],"distinguish":[91],"between":[92],"reliable":[93],"unreliable":[95],"unlabeled":[96],"samples.":[97],"To":[98],"address":[99],"this":[100],"limitation,":[101],"we":[102,142],"propose":[103],"hardness-aware":[105,139],"curriculum":[106,130,196],"framework":[108,198],"dynamically":[110],"selects":[111],"pseudo-labeled":[112],"samples":[113],"based":[114],"their":[116],"difficulty,":[117],"progressing":[118],"easy":[120],"complex":[122],"examples.":[123],"We":[124],"introduce":[125,163],"both":[126],"multi-stage":[127],"adaptive":[129],"strategies":[131],"replace":[133],"fixed-threshold":[134],"more":[137],"flexible,":[138],"mechanisms.":[140],"Additionally,":[141],"present":[143],"novel":[145],"structured":[146,200],"augmentation":[148,201],"strategy":[149],"specifically":[150],"tailored":[151],"estimation,":[154],"which":[155],"assembles":[156],"composite":[157],"augmented":[160],"patches":[161],"feature":[164],"diversity":[165],"while":[166],"preserving":[167],"critical":[168],"geometric":[169],"integrity.":[170],"Comprehensive":[171],"experiments":[172],"PASCAL3D+":[174],"ObjectNet3D":[176],"demonstrate":[177],"our":[179,195],"method":[180],"outperforms":[181],"existing":[182],"supervised":[183],"baselines,":[186],"particularly":[187],"low-data":[189],"regimes,":[190],"validating":[191],"the":[192],"effectiveness":[193],"approach.":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-25T00:00:00"}
