{"id":"https://openalex.org/W3036164064","doi":null,"title":"Adversarial Transfer of Pose Estimation Regression","display_name":"Adversarial Transfer of Pose Estimation Regression","publication_year":2020,"publication_date":"2020-06-20","ids":{"openalex":"https://openalex.org/W3036164064","mag":"3036164064"},"language":"en","primary_location":{"id":"mag:3036164064","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.11658","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":"http://export.arxiv.org/pdf/2006.11658","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034733444","display_name":"Boris Chidlovskii Assem Sadek","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Boris Chidlovskii Assem Sadek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5034733444"],"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7592999935150146,"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":0.7592999935150146,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.1914999932050705,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.03350000083446503,"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/camera-pose-estimation","display_name":"camera pose estimation","score":0.9959999918937683},{"id":"https://openalex.org/keywords/visual-localization","display_name":"visual localization","score":0.9599999785423279},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.7549999952316284},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"adversarial learning","score":0.8130000233650208},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.7730000019073486},{"id":"https://openalex.org/keywords/distribution-shift","display_name":"distribution shift","score":0.902999997138977},{"id":"https://openalex.org/keywords/self-supervised-learning","display_name":"self-supervised learning","score":0.906000018119812}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7603904008865356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7342747449874878},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6205434799194336},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5729948878288269},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5582705736160278},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.524241030216217},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4946138560771942},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4622277021408081},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.45787522196769714},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.44983798265457153},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.44755250215530396},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41999685764312744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3967876434326172},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35155582427978516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1355472207069397},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.08302360773086548},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07349768280982971},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3036164064","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.11658","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:3036164064","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.11658","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W158260078","https://openalex.org/W1731081199","https://openalex.org/W1989476314","https://openalex.org/W2031342017","https://openalex.org/W2057266281","https://openalex.org/W2117228865","https://openalex.org/W2122347864","https://openalex.org/W2159291411","https://openalex.org/W2200124539","https://openalex.org/W2279895976","https://openalex.org/W2413199960","https://openalex.org/W2556455135","https://openalex.org/W2584731199","https://openalex.org/W2605111497","https://openalex.org/W2739492061","https://openalex.org/W2739759330","https://openalex.org/W2768185495","https://openalex.org/W2785325870","https://openalex.org/W2786808285","https://openalex.org/W2789698879","https://openalex.org/W2793745122","https://openalex.org/W2795645133","https://openalex.org/W2798302276","https://openalex.org/W2798593490","https://openalex.org/W2885722640","https://openalex.org/W2892805284","https://openalex.org/W2892865870","https://openalex.org/W2905913346","https://openalex.org/W2913939497","https://openalex.org/W2946812986","https://openalex.org/W2948069880","https://openalex.org/W2949280493","https://openalex.org/W2949948647","https://openalex.org/W2962835731","https://openalex.org/W2982101479","https://openalex.org/W3091598621","https://openalex.org/W6941453574"],"related_works":["https://openalex.org/W3217710822","https://openalex.org/W2981489086","https://openalex.org/W3182969629","https://openalex.org/W4309799831","https://openalex.org/W4312888163","https://openalex.org/W3011401378","https://openalex.org/W3202933889","https://openalex.org/W3154420310","https://openalex.org/W6941453574","https://openalex.org/W7222979342"],"abstract_inverted_index":{"We":[0,41,97,119,144],"address":[1],"the":[2,25,29,43,72,121,128,133,165,168],"problem":[3],"of":[4,28,63,135,138,167],"camera":[5,89],"pose":[6,15,64,90],"estimation":[7,16,65],"in":[8,71,140],"visual":[9],"localization.":[10],"Current":[11],"regression-based":[12],"methods":[13],"for":[14,83,103,116],"are":[17],"trained":[18],"and":[19,32,39,51,75,85,108,126,154,162],"evaluated":[20],"scene-wise.":[21],"They":[22],"depend":[23],"on":[24,148],"coordinate":[26],"frame":[27],"training":[30],"dataset":[31,44],"show":[33],"a":[34,60,94,99],"low":[35],"generalization":[36,50],"across":[37],"scenes":[38],"datasets.":[40],"identify":[42],"shift":[45],"an":[46,56],"important":[47],"barrier":[48],"to":[49,88,112,131,164],"consider":[52],"transfer":[53],"learning":[54,104,111,125],"as":[55],"alternative":[57],"way":[58],"towards":[59],"better":[61],"reuse":[62],"models.":[66],"%To":[67],"benefit":[68],"from":[69],"%for":[70],"image":[73,106],"classification":[74,84],"semantic":[76],"segmentation.":[77],"e":[78],"revise":[79],"domain":[80],"adaptation":[81,101],"techniques":[82],"extend":[86],"them":[87],"estimation,":[91],"which":[92],"is":[93],"multi-regression":[95],"task.":[96],"develop":[98],"deep":[100],"network":[102,122,147],"scene-invariant":[105,136],"representations":[107,115],"use":[109,127],"adversarial":[110],"generate":[113],"such":[114],"model":[117],"transfer.":[118],"enrich":[120],"with":[123],"self-supervised":[124],"adaptability":[129],"theory":[130],"validate":[132],"existence":[134],"representation":[137],"images":[139],"two":[141,149],"given":[142],"scenes.":[143],"evaluate":[145],"our":[146],"public":[150],"datasets,":[151],"Cambridge":[152],"Landmarks":[153],"7Scene,":[155],"demonstrate":[156],"its":[157],"superiority":[158],"over":[159],"several":[160],"baselines":[161],"compare":[163],"state":[166],"art":[169],"methods.":[170]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2020-06-25T00:00:00"}