{"id":"https://openalex.org/W3200732573","doi":"https://doi.org/10.1109/icra46639.2022.9812288","title":"MotionHint: Self-Supervised Monocular Visual Odometry with Motion Constraints","display_name":"MotionHint: Self-Supervised Monocular Visual Odometry with Motion Constraints","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W3200732573","doi":"https://doi.org/10.1109/icra46639.2022.9812288","mag":"3200732573"},"language":"en","primary_location":{"id":"doi:10.1109/icra46639.2022.9812288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812288","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","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 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100390548","display_name":"Cong Wang","orcid":"https://orcid.org/0009-0009-2584-5222"},"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":"Cong Wang","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China","Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339128","display_name":"Yu-Ping Wang","orcid":"https://orcid.org/0000-0003-4129-7704"},"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":"Yu-Ping Wang","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China","Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004194238","display_name":"Dinesh Manocha","orcid":"https://orcid.org/0000-0001-7047-9801"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dinesh Manocha","raw_affiliation_strings":["Computer Engineering at the University of Maryland,Department of Computer Science and Electrical,MD,USA,20742"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering at the University of Maryland,Department of Computer Science and Electrical,MD,USA,20742","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.2815,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.98544813,"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":"1265","last_page":"1272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998000264167786,"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":0.9998000264167786,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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":0.9934999942779541,"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/visual-odometry","display_name":"Visual odometry","score":0.8955749869346619},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.8501361608505249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7693057060241699},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7373238801956177},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.7059024572372437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6713897585868835},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6030066609382629},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5774018168449402},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4414404332637787},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4364960789680481},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4326433837413788},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.29464173316955566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2057218849658966}],"concepts":[{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.8955749869346619},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.8501361608505249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7693057060241699},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7373238801956177},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.7059024572372437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6713897585868835},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6030066609382629},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5774018168449402},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4414404332637787},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4364960789680481},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4326433837413788},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.29464173316955566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2057218849658966},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra46639.2022.9812288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812288","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","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 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:doi:10.48550/arxiv.2109.06768","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2109.06768","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G510611830","display_name":null,"funder_award_id":"61872210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W612478963","https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1612997784","https://openalex.org/W1970504153","https://openalex.org/W2015996585","https://openalex.org/W2064675550","https://openalex.org/W2150066425","https://openalex.org/W2400202024","https://openalex.org/W2474281075","https://openalex.org/W2535547924","https://openalex.org/W2561074213","https://openalex.org/W2598706937","https://openalex.org/W2600383743","https://openalex.org/W2609883120","https://openalex.org/W2950517871","https://openalex.org/W2963583471","https://openalex.org/W2963962620","https://openalex.org/W2964314455","https://openalex.org/W2964339591","https://openalex.org/W2967321219","https://openalex.org/W2970971581","https://openalex.org/W2971000934","https://openalex.org/W2981518351","https://openalex.org/W2982102242","https://openalex.org/W2985775862","https://openalex.org/W3035056458","https://openalex.org/W3096240490","https://openalex.org/W3102327032","https://openalex.org/W3103648783","https://openalex.org/W3105431515","https://openalex.org/W3106440972","https://openalex.org/W3108746553","https://openalex.org/W3173472634","https://openalex.org/W3174211490","https://openalex.org/W3208092997","https://openalex.org/W4295312788","https://openalex.org/W6628877408","https://openalex.org/W6721610202","https://openalex.org/W6735443497","https://openalex.org/W6766978945","https://openalex.org/W6767088534","https://openalex.org/W6781026343","https://openalex.org/W6785114638"],"related_works":["https://openalex.org/W2610028676","https://openalex.org/W2789598255","https://openalex.org/W2126722086","https://openalex.org/W2962781507","https://openalex.org/W2757468587","https://openalex.org/W2219787495","https://openalex.org/W2085689676","https://openalex.org/W2739783344","https://openalex.org/W4296947528","https://openalex.org/W3200732573"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,60],"novel":[3],"self-supervised":[4,36,51,84],"algorithm":[5,118,130],"named":[6,63],"MotionHint":[7,117,129],"for":[8],"monocular":[9,37],"visual":[10],"odometry":[11],"(VO)":[12],"that":[13,32,127],"takes":[14],"motion":[15,30,55,92],"constraints":[16],"into":[17],"account.":[18],"A":[19],"key":[20],"aspect":[21],"of":[22,74,80],"our":[23,112,116,128],"approach":[24,85],"is":[25,57,66,95],"to":[26,41,45,68,135,141,153],"use":[27],"an":[28],"appropriate":[29],"model":[31,56],"can":[33,131],"help":[34],"existing":[35,108,136],"VO":[38],"(SSM-VO)":[39],"algorithms":[40],"overcome":[42],"issues":[43],"related":[44],"the":[46,71,75,78,87,91,96,100,103,120,144,148],"local":[47],"minima":[48],"within":[49],"their":[50],"loss":[52,89],"functions.":[53],"The":[54],"expressed":[58],"with":[59],"neural":[61],"network":[62],"PPnet.":[64],"It":[65],"trained":[67],"coarsely":[69],"predict":[70],"next":[72],"pose":[73],"camera":[76],"and":[77,90,102],"uncertainty":[79],"this":[81],"prediction.":[82],"Our":[83],"combines":[86],"original":[88],"loss,":[93],"which":[94],"weighted":[97],"difference":[98],"between":[99],"prediction":[101],"generated":[104],"ego-motion.":[105],"Taking":[106],"two":[107],"SSM-VO":[109,139],"systems":[110,140],"as":[111],"baseline,":[113],"we":[114],"evaluate":[115],"on":[119],"standard":[121],"KITTI":[122],"benchmark.":[123],"Experimental":[124],"results":[125],"show":[126],"be":[132],"easily":[133],"applied":[134],"open-sourced":[137],"state-of-the-art":[138],"greatly":[142],"improve":[143],"performance":[145],"by":[146,151],"reducing":[147],"resulting":[149],"ATE":[150],"up":[152],"28.73%.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2022-10-04T00:00:00"}
