{"id":"https://openalex.org/W3015439351","doi":"https://doi.org/10.1109/icassp40776.2020.9052903","title":"Spatio-Temporal and Geometry Constrained Network for Automobile Visual Odometry","display_name":"Spatio-Temporal and Geometry Constrained Network for Automobile Visual Odometry","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015439351","doi":"https://doi.org/10.1109/icassp40776.2020.9052903","mag":"3015439351"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9052903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100410326","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-7498-6541"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101990146","display_name":"Wei Peng","orcid":"https://orcid.org/0000-0002-4994-8965"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wei","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036081371","display_name":"Weibo Huang","orcid":"https://orcid.org/0000-0002-9583-1944"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weibo Huang","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038970887","display_name":"Guoliang Hua","orcid":"https://orcid.org/0000-0003-4666-8551"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Hua","raw_affiliation_strings":["Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038040039","display_name":"Fanyang Meng","orcid":"https://orcid.org/0000-0001-5725-2178"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanyang Meng","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04019639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"2747","last_page":"2751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994999766349792,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9965000152587891,"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":0.8241620063781738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7475489974021912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7290905117988586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7016429901123047},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.6919638514518738},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5991940498352051},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.5697560906410217},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.512153148651123},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3272772431373596},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.25471293926239014}],"concepts":[{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.8241620063781738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7475489974021912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7290905117988586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7016429901123047},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.6919638514518738},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5991940498352051},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.5697560906410217},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.512153148651123},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3272772431373596},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.25471293926239014},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9052903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W612478963","https://openalex.org/W764651262","https://openalex.org/W1485009520","https://openalex.org/W1612997784","https://openalex.org/W1970504153","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2121196976","https://openalex.org/W2150066425","https://openalex.org/W2155695215","https://openalex.org/W2168676389","https://openalex.org/W2220063164","https://openalex.org/W2400202024","https://openalex.org/W2589138733","https://openalex.org/W2598706937","https://openalex.org/W2605111497","https://openalex.org/W2609883120","https://openalex.org/W2686318547","https://openalex.org/W2752605215","https://openalex.org/W2765767940","https://openalex.org/W2770446450","https://openalex.org/W2792140610","https://openalex.org/W2795645133","https://openalex.org/W2936831171","https://openalex.org/W2963962620","https://openalex.org/W2964019655","https://openalex.org/W2964206229","https://openalex.org/W3103648783","https://openalex.org/W3106440972","https://openalex.org/W6674330103","https://openalex.org/W6733816241","https://openalex.org/W6755828627"],"related_works":["https://openalex.org/W2979950214","https://openalex.org/W87609089","https://openalex.org/W3024737167","https://openalex.org/W2414561716","https://openalex.org/W3161199934","https://openalex.org/W2303855011","https://openalex.org/W2312326526","https://openalex.org/W2412578866","https://openalex.org/W3105866016","https://openalex.org/W4312703710"],"abstract_inverted_index":{"Visual":[0],"odometry":[1],"(VO)":[2],"is":[3,64,73,99,134],"an":[4,54],"essence":[5],"of":[6,34],"vision-based":[7],"localization":[8],"and":[9,18,24,40,61,125,152],"mapping":[10],"system":[11],"where":[12],"existing":[13],"learning-based":[14],"approaches":[15],"utilize":[16],"CNN":[17],"RNN":[19],"to":[20,75,101],"model":[21,159],"camera":[22,104],"motion":[23,79,105,110],"gain":[25],"promising":[26],"results.":[27],"However,":[28],"these":[29,52],"methods":[30],"lack":[31],"full":[32],"use":[33],"the":[35,77,83,89,103,108,120,126,137,157],"relationship":[36],"between":[37],"spatial":[38,69],"characteristics":[39],"temporal":[41,95],"clues,":[42],"as":[43,45],"well":[44],"geometry":[46,114],"constraints":[47],"in":[48],"VO.":[49],"To":[50],"overcome":[51],"deficiencies,":[53],"end-to-end":[55],"framework":[56],"that":[57,118,156],"leverages":[58],"spatio-temporal":[59],"relevance":[60],"geometrical":[62],"knowledge":[63],"proposed.":[65],"In":[66],"particular,":[67],"a":[68,113,131],"response":[70,96],"module":[71,93,97],"(SRM)":[72],"designed":[74],"extract":[76],"visual":[78],"features":[80],"by":[81],"emphasizing":[82],"most":[84],"interconnected":[85],"regions":[86],"while":[87],"suppressing":[88],"irrelevant":[90],"areas.":[91],"A":[92],"named":[94],"(TRM)":[98],"used":[100],"regress":[102],"via":[106],"adopting":[107],"optimal":[109],"features.":[111],"Moreover,":[112],"constrained":[115],"(GC)":[116],"loss":[117,139],"minimizes":[119],"estimated":[121],"inter-frame":[122],"pose":[123,128],"errors":[124,129],"accumulated":[127],"within":[130],"local":[132],"period":[133],"introduced.":[135],"Actually,":[136],"GC":[138],"utilizes":[140],"adaptive":[141],"learnable":[142],"balance":[143],"factors":[144],"for":[145],"balancing":[146],"losses.":[147],"Experimental":[148],"results":[149],"on":[150],"KITTI":[151],"Malaga":[153],"datasets":[154],"demonstrate":[155],"proposed":[158],"outperforms":[160],"state-of-the-art":[161],"monocular":[162],"methods.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
