{"id":"https://openalex.org/W2919859960","doi":"https://doi.org/10.1145/3297067.3297094","title":"Unsupervised Depth Estimation from Monocular Video based on Relative Motion","display_name":"Unsupervised Depth Estimation from Monocular Video based on Relative Motion","publication_year":2018,"publication_date":"2018-11-28","ids":{"openalex":"https://openalex.org/W2919859960","doi":"https://doi.org/10.1145/3297067.3297094","mag":"2919859960"},"language":"en","primary_location":{"id":"doi:10.1145/3297067.3297094","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297067.3297094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Signal Processing and Machine Learning","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/A5024373783","display_name":"Hui Cao","orcid":"https://orcid.org/0000-0002-1896-5201"},"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":true,"raw_author_name":"Hui Cao","raw_affiliation_strings":["School of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407102","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0003-1288-2621"},"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":"Chao Wang","raw_affiliation_strings":["School of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338672","display_name":"Ping Wang","orcid":"https://orcid.org/0000-0002-6917-6050"},"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":"Ping Wang","raw_affiliation_strings":["School of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080936291","display_name":"Qingquan Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159565","display_name":"SAIC Motor (China)","ror":"https://ror.org/051b9ta18","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159565"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingquan Zou","raw_affiliation_strings":["Research & Advanced Technology Department, SAIC Motor Corporation Limited, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Research & Advanced Technology Department, SAIC Motor Corporation Limited, Shanghai, China","institution_ids":["https://openalex.org/I4210159565"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100451727","display_name":"Xiao Xiao","orcid":"https://orcid.org/0000-0002-4328-0634"},"institutions":[{"id":"https://openalex.org/I4210159565","display_name":"SAIC Motor (China)","ror":"https://ror.org/051b9ta18","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159565"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Xiao","raw_affiliation_strings":["Research & Advanced Technology Department, SAIC Motor Corporation Limited, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Research & Advanced Technology Department, SAIC Motor Corporation Limited, Shanghai, China","institution_ids":["https://openalex.org/I4210159565"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5024373783"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19023268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"159","last_page":"165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994999766349792,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8504127264022827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.775049090385437},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7702270746231079},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.70929354429245},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6124624609947205},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.573081910610199},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.536461353302002},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5105503797531128},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4804122745990753},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.45215603709220886}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8504127264022827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.775049090385437},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7702270746231079},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.70929354429245},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6124624609947205},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.573081910610199},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.536461353302002},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5105503797531128},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4804122745990753},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.45215603709220886},{"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:10.1145/3297067.3297094","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297067.3297094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Signal Processing and Machine Learning","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":34,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W612478963","https://openalex.org/W1612997784","https://openalex.org/W1803059841","https://openalex.org/W1984190176","https://openalex.org/W2117228865","https://openalex.org/W2125416623","https://openalex.org/W2127578024","https://openalex.org/W2146881125","https://openalex.org/W2150066425","https://openalex.org/W2151103935","https://openalex.org/W2151290401","https://openalex.org/W2271840356","https://openalex.org/W2339763956","https://openalex.org/W2354576866","https://openalex.org/W2461937780","https://openalex.org/W2474281075","https://openalex.org/W2511730936","https://openalex.org/W2520707372","https://openalex.org/W2606794968","https://openalex.org/W2608018946","https://openalex.org/W2609883120","https://openalex.org/W2750632489","https://openalex.org/W2785512290","https://openalex.org/W2798410215","https://openalex.org/W2949634581","https://openalex.org/W2951234442","https://openalex.org/W2962741876","https://openalex.org/W2963583471","https://openalex.org/W3100388886","https://openalex.org/W3103648783","https://openalex.org/W3124420883","https://openalex.org/W4236965008","https://openalex.org/W4256426301"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W4387967917","https://openalex.org/W1647606319","https://openalex.org/W4307623796","https://openalex.org/W4394784820"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,89],"present":[4],"an":[5],"unsupervised":[6],"learning":[7],"based":[8],"approach":[9],"to":[10,33,48,103,118,132],"conduct":[11],"depth":[12,36,135],"estimation":[13],"for":[14],"monocular":[15],"camera":[16,55,82],"video":[17,59],"images.":[18],"Our":[19],"system":[20],"is":[21,31,84],"formed":[22],"by":[23,73,86],"two":[24,113,128],"convolutional":[25],"neural":[26],"networks":[27,114],"(CNNs).":[28],"A":[29],"Depth-net":[30],"applied":[32],"estimate":[34,49,104],"the":[35,41,50,54,74,87,94,101,105,112,127],"information":[37],"of":[38,53,93,96,111],"objects":[39,71,98],"in":[40],"target":[42],"frame,":[43],"and":[44,99],"a":[45,80,120],"Pose-net":[46,102],"tends":[47],"relative":[51,107],"motion":[52],"from":[56,62],"multiple":[57],"adjacent":[58],"frames.":[60],"Different":[61],"most":[63,149],"previous":[64],"works,":[65],"which":[66,126],"normally":[67],"assume":[68],"that":[69,79,141],"all":[70,97],"captured":[72],"images":[75],"are":[76,115,130],"static":[77],"so":[78],"frame-level":[81],"pose":[83],"generated":[85],"Pose-net,":[88],"take":[90],"into":[91],"account":[92],"motions":[95],"require":[100],"pixel-level":[106],"pose.":[108],"The":[109],"outputs":[110],"then":[116],"combined":[117],"formulate":[119],"synthetic":[121],"view":[122],"loss":[123],"function,":[124],"through":[125],"CNNs":[129],"optimized":[131],"provide":[133,145],"accurate":[134],"estimation.":[136],"Experimental":[137],"test":[138],"results":[139],"show":[140],"our":[142],"method":[143],"can":[144],"better":[146],"performance":[147],"than":[148],"conventional":[150],"approaches.":[151]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}