{"id":"https://openalex.org/W2774618166","doi":null,"title":"Unsupervised Domain Adaptation for 3D Keypoint Prediction from a Single Depth Scan.","display_name":"Unsupervised Domain Adaptation for 3D Keypoint Prediction from a Single Depth Scan.","publication_year":2017,"publication_date":"2017-12-15","ids":{"openalex":"https://openalex.org/W2774618166","mag":"2774618166"},"language":"en","primary_location":{"id":"mag:2774618166","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1712.05765v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/1712.05765v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103170520","display_name":"Xingyi Zhou","orcid":"https://orcid.org/0000-0002-0914-8525","observed_orcids":["https://orcid.org/0000-0002-0914-8525"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingyi Zhou","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0914-8525","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086235030","display_name":"Arjun Karpur","orcid":"https://orcid.org/0000-0002-7568-3550","observed_orcids":["https://orcid.org/0000-0002-7568-3550"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arjun Karpur","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7568-3550","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040877128","display_name":"Chuang Gan","orcid":"https://orcid.org/0000-0003-4031-5886","observed_orcids":["https://orcid.org/0000-0003-4031-5886"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuang Gan","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4031-5886","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081407963","display_name":"Linjie Luo","orcid":"https://orcid.org/0000-0001-6322-1175","observed_orcids":["https://orcid.org/0000-0001-6322-1175"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Linjie Luo","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6322-1175","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056540212","display_name":"Qixing Huang","orcid":"https://orcid.org/0000-0001-6365-8051","observed_orcids":["https://orcid.org/0000-0001-6365-8051","https://orcid.org/0009-0001-7908-7174","https://orcid.org/0000-0003-3452-1202"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qixing Huang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6365-8051","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":9,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9926999807357788,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9926999807357788,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0010000000474974513,"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/unsupervised-domain-adaptation","display_name":"unsupervised domain adaptation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/geometric-alignment","display_name":"geometric alignment","score":0.8209999799728394},{"id":"https://openalex.org/keywords/alternating-optimization","display_name":"alternating optimization","score":0.8330000042915344},{"id":"https://openalex.org/keywords/unlabeled-target-domain","display_name":"unlabeled target domain","score":0.5210000276565552},{"id":"https://openalex.org/keywords/3d-human-pose-estimation","display_name":"3D human pose estimation","score":0.7390000224113464}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.760045051574707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7256239652633667},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6799497604370117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6737295985221863},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5459363460540771},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5392701625823975},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5336844325065613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5083205103874207},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5048926472663879},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4668216109275818},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4596535563468933},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42731642723083496},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4134311378002167},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3309425711631775},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20104026794433594},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2774618166","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1712.05765v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2774618166","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1712.05765v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W116751493","https://openalex.org/W158943247","https://openalex.org/W1520757484","https://openalex.org/W1569530544","https://openalex.org/W1591870335","https://openalex.org/W1920022804","https://openalex.org/W1949568868","https://openalex.org/W1953319329","https://openalex.org/W1993267444","https://openalex.org/W2101032778","https://openalex.org/W2190691619","https://openalex.org/W2229637417","https://openalex.org/W2253156915","https://openalex.org/W2307770531","https://openalex.org/W2342277278","https://openalex.org/W2345308174","https://openalex.org/W2495603374","https://openalex.org/W2551540143","https://openalex.org/W2557465155","https://openalex.org/W2557626841","https://openalex.org/W2558385255","https://openalex.org/W2563100679","https://openalex.org/W2584009249","https://openalex.org/W2604375920","https://openalex.org/W2607512710","https://openalex.org/W2609026071","https://openalex.org/W2609211631","https://openalex.org/W2739759330","https://openalex.org/W2748259506","https://openalex.org/W2756050327","https://openalex.org/W2756073160","https://openalex.org/W2779610669","https://openalex.org/W2780638627","https://openalex.org/W2793814912","https://openalex.org/W2949070976","https://openalex.org/W2949650786","https://openalex.org/W2949987290","https://openalex.org/W2950634055","https://openalex.org/W2951900634","https://openalex.org/W2962759496","https://openalex.org/W2963097270","https://openalex.org/W2963500702","https://openalex.org/W2964285681"],"related_works":["https://openalex.org/W2883939894","https://openalex.org/W2982291417","https://openalex.org/W4399151446","https://openalex.org/W3047171008","https://openalex.org/W7107868415","https://openalex.org/W3177345794","https://openalex.org/W2971667760","https://openalex.org/W4399631183","https://openalex.org/W4313160354","https://openalex.org/W4311615006"],"abstract_inverted_index":{"In":[0,60],"this":[1],"paper,":[2],"we":[3,62],"introduce":[4,63],"a":[5,19,64],"novel":[6],"unsupervised":[7],"domain":[8,109],"adaptation":[9,110],"technique":[10],"for":[11,54],"the":[12,29,37,72,88],"task":[13],"of":[14,36,90],"3D":[15],"keypoint":[16,55],"prediction":[17,56],"from":[18,33],"single":[20],"depth":[21],"scan/image.":[22],"Our":[23],"key":[24],"idea":[25],"is":[26,104],"to":[27,68,106],"utilize":[28],"fact":[30],"that":[31,101],"predictions":[32,70],"different":[34],"views":[35],"same":[38],"or":[39],"similar":[40],"objects":[41],"should":[42],"be":[43,80],"consistent":[44],"with":[45],"each":[46],"other.":[47],"Such":[48],"view":[49],"consistency":[50],"provides":[51],"effective":[52],"regularization":[53],"on":[57,93],"unlabeled":[58],"instances.":[59],"addition,":[61],"geometric":[65],"alignment":[66],"term":[67],"regularize":[69],"in":[71],"target":[73],"domain.":[74],"The":[75],"resulting":[76],"loss":[77],"function":[78],"can":[79],"effectively":[81],"optimized":[82],"via":[83],"alternating":[84],"minimization.":[85],"We":[86],"demonstrate":[87],"effectiveness":[89],"our":[91,102],"approach":[92,103],"real":[94],"datasets":[95],"and":[96],"present":[97],"experimental":[98],"results":[99],"showing":[100],"superior":[105],"state-of-the-art":[107],"general-purpose":[108],"techniques.":[111]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2017-12-22T00:00:00"}