{"id":"https://openalex.org/W7159627205","doi":"https://doi.org/10.48550/arxiv.2604.27448","title":"LA-Pose: Latent Action Pretraining Meets Pose Estimation","display_name":"LA-Pose: Latent Action Pretraining Meets Pose Estimation","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7159627205","doi":"https://doi.org/10.48550/arxiv.2604.27448"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.27448","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27448","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.27448","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134946111","display_name":"Zhengqing Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Zhengqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060365441","display_name":"Saurabh Nair","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nair, Saurabh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068305183","display_name":"Prajwal Chidananda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chidananda, Prajwal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093192252","display_name":"Pujith Kachana","orcid":"https://orcid.org/0009-0000-0671-5902"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kachana, Pujith","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076180745","display_name":"Samuel Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Samuel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100785126","display_name":"Matthew Brown","orcid":"https://orcid.org/0000-0003-3045-2609"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brown, Matthew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067250964","display_name":"Yasutaka Furukawa","orcid":"https://orcid.org/0009-0006-9775-4512"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Furukawa, Yasutaka","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5134946111"],"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/T10812","display_name":"Human Pose and Action Recognition","score":0.4659000039100647,"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":0.4659000039100647,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.3393000066280365,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.027799999341368675,"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/pose","display_name":"Pose","score":0.7584999799728394},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6758000254631042},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5557000041007996},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4535999894142151},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3919999897480011},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.3903999924659729},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.36959999799728394},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.35010001063346863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7888000011444092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7756999731063843},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7584999799728394},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6758000254631042},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5557000041007996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.542900025844574},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4535999894142151},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.3903999924659729},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38940000534057617},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.265500009059906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2630999982357025}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.27448","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27448","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.27448","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27448","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,107],"paper":[1],"revisits":[2],"camera":[3,95],"pose":[4,96,113,156,179],"estimation":[5],"through":[6],"the":[7,21,87,146,168,172],"lens":[8],"of":[9,24,70,75,103,139,174],"self-supervised":[10,176],"pretraining,":[11],"focusing":[12],"on":[13,99,121,145],"inverse-dynamics":[14,175],"pretraining":[15],"as":[16,67,73,91],"a":[17,94,100],"scalable":[18],"alternative":[19],"to":[20,38,44,93,133,170],"current":[22],"trend":[23],"fully":[25],"supervised":[26],"training":[27],"with":[28],"3D":[29,105],"annotations.":[30,106],"Concretely,":[31,144],"we":[32],"employ":[33],"inverse-":[34],"and":[35,111,129,148],"forward-dynamics":[36],"models":[37],"learn":[39],"latent":[40,59,88],"action":[41,68,77,89],"representations,":[42],"similar":[43],"Genie":[45],"from":[46],"large-scale":[47],"driving":[48,122],"videos.":[49],"Our":[50,82],"idea":[51],"is":[52,167],"simple":[53],"yet":[54],"effective.":[55],"Existing":[56],"methods":[57,135],"use":[58],"actions":[60],"in":[61,79],"their":[62],"original":[63],"capacity,":[64],"that":[65,125],"is,":[66],"conditioning":[69],"world-models":[71],"or":[72],"proxies":[74],"robot":[76],"parameters":[78],"policy":[80],"networks.":[81],"method,":[83],"dubbed":[84],"LA-Pose,":[85],"repurposes":[86],"features":[90],"inputs":[92],"estimator,":[97],"finetuned":[98],"limited":[101],"set":[102],"high-quality":[104],"formulation":[108],"enables":[109],"accurate":[110],"generalizable":[112],"prediction":[114],"while":[115,136],"maintaining":[116],"feed-forward":[117,160],"efficiency.":[118],"Extensive":[119],"experiments":[120],"benchmarks":[123],"show":[124],"LA-Pose":[126,151],"achieves":[127,152],"competitive":[128],"even":[130],"superior":[131],"performance":[132],"state-of-the-art":[134],"using":[137],"orders":[138],"magnitude":[140],"less":[141],"labeled":[142],"data.":[143],"Waymo":[147],"PandaSet":[149],"benchmarks,":[150],"over":[153],"10%":[154],"higher":[155],"accuracy":[157],"than":[158],"recent":[159],"methods.":[161],"To":[162],"our":[163],"knowledge,":[164],"this":[165],"work":[166],"first":[169],"demonstrate":[171],"power":[173],"learning":[177],"for":[178],"estimation.":[180]},"counts_by_year":[],"updated_date":"2026-05-02T06:10:54.344120","created_date":"2026-05-02T00:00:00"}
