{"id":"https://openalex.org/W4313024976","doi":"https://doi.org/10.1109/cvpr52688.2022.02033","title":"Egocentric Prediction of Action Target in 3D","display_name":"Egocentric Prediction of Action Target in 3D","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4313024976","doi":"https://doi.org/10.1109/cvpr52688.2022.02033"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52688.2022.02033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.02033","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100346324","display_name":"Yiming Li","orcid":"https://orcid.org/0000-0002-0157-6218"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiming Li","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040805922","display_name":"Ziang Cao","orcid":"https://orcid.org/0000-0002-5682-9446"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziang Cao","raw_affiliation_strings":["Tongji University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049415137","display_name":"Andrew S. Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Liang","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033134454","display_name":"Benjamin Liang","orcid":"https://orcid.org/0000-0001-5365-4479"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Liang","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003753963","display_name":"Luoyao Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luoyao Chen","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104009095","display_name":"Hang Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Zhao","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100699151","display_name":"Chen Feng","orcid":"https://orcid.org/0000-0003-3211-1576"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Feng","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100346324"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":1.1222,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.854841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"20971","last_page":"20980"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994999766349792,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9972000122070312,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7604486346244812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7598720788955688},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6550604104995728},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5606910586357117},{"id":"https://openalex.org/keywords/workspace","display_name":"Workspace","score":0.5345543622970581},{"id":"https://openalex.org/keywords/multimodality","display_name":"Multimodality","score":0.5109433531761169},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.48935049772262573},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46779876947402954},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4330526292324066},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.43132826685905457},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.42766982316970825},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42687588930130005},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.42555558681488037},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42119327187538147},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4101904332637787},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33768048882484436},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07723769545555115}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7604486346244812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598720788955688},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6550604104995728},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5606910586357117},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.5345543622970581},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.5109433531761169},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.48935049772262573},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46779876947402954},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4330526292324066},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.43132826685905457},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.42766982316970825},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42687588930130005},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42555558681488037},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42119327187538147},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4101904332637787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33768048882484436},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07723769545555115},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","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/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52688.2022.02033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.02033","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W1970629627","https://openalex.org/W2026112871","https://openalex.org/W2055227894","https://openalex.org/W2071711566","https://openalex.org/W2082322650","https://openalex.org/W2120645068","https://openalex.org/W2147806277","https://openalex.org/W2165605600","https://openalex.org/W2198667788","https://openalex.org/W2204609240","https://openalex.org/W2212494831","https://openalex.org/W2293698677","https://openalex.org/W2396252981","https://openalex.org/W2412074020","https://openalex.org/W2443846596","https://openalex.org/W2461911683","https://openalex.org/W2519019567","https://openalex.org/W2528383574","https://openalex.org/W2554779556","https://openalex.org/W2605973302","https://openalex.org/W2618928235","https://openalex.org/W2741156154","https://openalex.org/W2775266474","https://openalex.org/W2776330782","https://openalex.org/W2796136333","https://openalex.org/W2893375469","https://openalex.org/W2894504664","https://openalex.org/W2895143214","https://openalex.org/W2895649888","https://openalex.org/W2897187502","https://openalex.org/W2914139746","https://openalex.org/W2945792291","https://openalex.org/W2962875398","https://openalex.org/W2963082988","https://openalex.org/W2963231572","https://openalex.org/W2963337691","https://openalex.org/W2963675021","https://openalex.org/W2963798496","https://openalex.org/W2967171277","https://openalex.org/W2971672253","https://openalex.org/W2971680695","https://openalex.org/W2983465317","https://openalex.org/W2989839235","https://openalex.org/W2993447238","https://openalex.org/W2994662721","https://openalex.org/W3021013305","https://openalex.org/W3021065276","https://openalex.org/W3034891989","https://openalex.org/W3035367723","https://openalex.org/W3092798182","https://openalex.org/W3106250896","https://openalex.org/W3107142155","https://openalex.org/W3109667662","https://openalex.org/W3119437694","https://openalex.org/W3123364653","https://openalex.org/W3144974485","https://openalex.org/W3177419066","https://openalex.org/W3191734489","https://openalex.org/W3205786327","https://openalex.org/W4214555767","https://openalex.org/W6687793295","https://openalex.org/W6688426012","https://openalex.org/W6712491454","https://openalex.org/W6718508886","https://openalex.org/W6749381375","https://openalex.org/W6749916090","https://openalex.org/W6755026235","https://openalex.org/W6755246496","https://openalex.org/W6776216169","https://openalex.org/W6776730017","https://openalex.org/W6780832159","https://openalex.org/W6784323626","https://openalex.org/W6785652829","https://openalex.org/W6786330475"],"related_works":["https://openalex.org/W4315750480","https://openalex.org/W2283162247","https://openalex.org/W4212983513","https://openalex.org/W2524507886","https://openalex.org/W2975200075","https://openalex.org/W2016398835","https://openalex.org/W2792760418","https://openalex.org/W3186584605","https://openalex.org/W4292103105","https://openalex.org/W3107115059"],"abstract_inverted_index":{"We":[0],"are":[1],"interested":[2],"in":[3,18,28,119],"anticipating":[4],"as":[5,7],"early":[6],"possible":[8],"the":[9],"target":[10],"location":[11],"of":[12,61,67,114],"a":[13,19,57],"person's":[14],"object":[15],"manipulation":[16],"action":[17],"3D":[20,82],"workspace":[21],"from":[22,40,84],"egocentric":[23,52],"vision.":[24],"It":[25],"is":[26,112],"important":[27],"fields":[29],"like":[30],"human-robot":[31],"collaboration,":[32],"but":[33],"has":[34],"not":[35],"yet":[36],"received":[37],"enough":[38],"attention":[39],"vision":[41,53],"and":[42,69,72,81,96,122],"learning":[43,123],"communities.":[44,124],"To":[45],"stimulate":[46],"more":[47,62],"research":[48],"on":[49,77],"this":[50,109],"challenging":[51],"task,":[54],"we":[55,88],"propose":[56],"large":[58],"multimodality":[59],"dataset":[60],"than":[63],"1":[64],"million":[65],"frames":[66],"RGB-D":[68],"IMU":[70],"streams,":[71],"provide":[73],"evaluation":[74],"metrics":[75],"based":[76],"our":[78],"high-quality":[79],"2D":[80],"labels":[83],"semi-automatic":[85],"annotation.":[86],"Meanwhile,":[87],"design":[89],"baseline":[90],"methods":[91],"using":[92],"recurrent":[93],"neural":[94],"networks":[95],"conduct":[97],"various":[98],"ablation":[99],"studies":[100],"to":[101],"validate":[102],"their":[103],"effectiveness.":[104],"Our":[105],"results":[106],"demonstrate":[107],"that":[108],"new":[110],"task":[111],"worthy":[113],"further":[115],"study":[116],"by":[117],"researchers":[118],"robotics,":[120],"vision,":[121]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
