{"id":"https://openalex.org/W4206171875","doi":"https://doi.org/10.1109/iros51168.2021.9636283","title":"VIPose: Real-time Visual-Inertial 6D Object Pose Tracking","display_name":"VIPose: Real-time Visual-Inertial 6D Object Pose Tracking","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W4206171875","doi":"https://doi.org/10.1109/iros51168.2021.9636283"},"language":"en","primary_location":{"id":"doi:10.1109/iros51168.2021.9636283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636283","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5040738964","display_name":"Rundong Ge","orcid":"https://orcid.org/0000-0002-3376-9129"},"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":"Rundong Ge","raw_affiliation_strings":["Tandon School of Engineering, New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"Tandon School of Engineering, New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077485450","display_name":"Giuseppe Loianno","orcid":"https://orcid.org/0000-0002-3263-5401"},"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":"Giuseppe Loianno","raw_affiliation_strings":["Tandon School of Engineering, New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"Tandon School of Engineering, New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040738964"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":3.3372,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.94211774,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4597","last_page":"4603"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9986000061035156,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9898999929428101,"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":0.9120035171508789},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8576370477676392},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7683405876159668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7525151968002319},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.6986439824104309},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.616549015045166},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5919199585914612},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.5495287179946899},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.48223742842674255},{"id":"https://openalex.org/keywords/augmented-reality","display_name":"Augmented reality","score":0.45470815896987915},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4048727750778198}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.9120035171508789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8576370477676392},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7683405876159668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7525151968002319},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.6986439824104309},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.616549015045166},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5919199585914612},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.5495287179946899},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.48223742842674255},{"id":"https://openalex.org/C153715457","wikidata":"https://www.wikidata.org/wiki/Q254183","display_name":"Augmented reality","level":2,"score":0.45470815896987915},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4048727750778198}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros51168.2021.9636283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636283","pdf_url":null,"source":{"id":"https://openalex.org/S4363607734","display_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320307798","display_name":"Nokia","ror":"https://ror.org/04pkc8m17"},{"id":"https://openalex.org/F4320308258","display_name":"Qualcomm","ror":"https://ror.org/002zrf773"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1505952289","https://openalex.org/W1526868886","https://openalex.org/W2051460003","https://openalex.org/W2058761328","https://openalex.org/W2064675550","https://openalex.org/W2101199297","https://openalex.org/W2194775991","https://openalex.org/W2519822546","https://openalex.org/W2557430988","https://openalex.org/W2600447016","https://openalex.org/W2768879211","https://openalex.org/W2781064046","https://openalex.org/W2792764867","https://openalex.org/W2795999188","https://openalex.org/W2895410314","https://openalex.org/W2952348863","https://openalex.org/W2963188159","https://openalex.org/W2963423603","https://openalex.org/W2963678509","https://openalex.org/W2963756608","https://openalex.org/W2964249569","https://openalex.org/W2989915422","https://openalex.org/W3038975720","https://openalex.org/W3090160518","https://openalex.org/W3101037136","https://openalex.org/W3130138602","https://openalex.org/W3133557228","https://openalex.org/W6630201400","https://openalex.org/W6631711059","https://openalex.org/W6749825310"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W4386075737","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W2088028039","https://openalex.org/W4382141741","https://openalex.org/W3165753266","https://openalex.org/W1968783203","https://openalex.org/W4206633503"],"abstract_inverted_index":{"Estimating":[0],"the":[1,41,55,80,91,106,155,194],"6D":[2,109,117,173],"pose":[3,34,36,56,82,110,118,131,174],"of":[4,93,154,197],"objects":[5,137],"is":[6,90,119,158],"beneficial":[7],"for":[8,134],"robotics":[9,23],"tasks":[10],"such":[11],"as":[12,17,19],"transportation,":[13],"autonomous":[14],"navigation,":[15],"manipulation":[16],"well":[18,140],"in":[20,85],"scenarios":[21],"beyond":[22],"like":[24],"virtual":[25],"and":[26,52,75,101,171],"augmented":[27],"reality.":[28],"With":[29],"respect":[30],"to":[31,47,53,78,104,142,146,189],"single":[32],"image":[33,113],"estimation,":[35],"tracking":[37,83],"takes":[38],"into":[39],"account":[40],"temporal":[42],"information":[43],"across":[44],"multiple":[45],"frames":[46],"overcome":[48],"possible":[49],"detection":[50],"inconsistencies":[51],"improve":[54],"estimation":[57,132],"efficiency.":[58],"In":[59],"this":[60],"work,":[61],"we":[62],"introduce":[63],"a":[64,94,161],"novel":[65,95],"Deep":[66],"Neural":[67],"Network":[68],"(DNN)":[69],"called":[70,164],"VIPose,":[71],"that":[72,138],"combines":[73],"inertial":[74,102],"camera":[76],"data":[77],"address":[79],"object":[81],"problem":[84],"real-time.":[86,199],"The":[87,115,152,183],"key":[88],"contribution":[89],"design":[92],"DNN":[96],"architecture":[97],"which":[98],"fuses":[99],"visual":[100],"features":[103],"predict":[105],"objects\u2019":[107],"relative":[108,125],"between":[111],"consecutive":[112],"frames.":[114],"overall":[116],"then":[120],"estimated":[121],"by":[122,148,177],"consecutively":[123],"combining":[124],"poses.":[126],"Our":[127],"approach":[128,157,184],"shows":[129],"remarkable":[130],"results":[133],"heavily":[135],"occluded":[136],"are":[139],"known":[141],"be":[143],"very":[144],"challenging":[145],"handle":[147],"existing":[149],"state-of-the-art":[150,190],"solutions.":[151],"effectiveness":[153],"proposed":[156],"validated":[159],"on":[160],"new":[162],"dataset":[163],"VIYCB":[165],"with":[166,193],"RGB":[167],"image,":[168],"IMU":[169],"data,":[170],"accurate":[172],"annotations":[175],"created":[176],"employing":[178],"an":[179],"automated":[180],"labeling":[181],"technique.":[182],"presents":[185],"accuracy":[186],"performances":[187],"comparable":[188],"techniques,":[191],"but":[192],"additional":[195],"benefit":[196],"being":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
