乐胖代购免代理版

{"id":"https://openalex.org/W3033080619","doi":"https://doi.org/10.1109/crv50864.2020.00023","title":"MASC-Net: Multi-scale Anisotropic Sparse Convolutional Network for Sparse Depth Densification","display_name":"MASC-Net: Multi-scale Anisotropic Sparse Convolutional Network for Sparse Depth Densification","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3033080619","doi":"https://doi.org/10.1109/crv50864.2020.00023","mag":"3033080619"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/crv50864.2020.00023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5102080545","display_name":"Seungchul Ryu","orcid":null},"institutions":[],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Seungchul Ryu","raw_affiliation_strings":["Airy3D Inc., Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Airy3D Inc., Montreal, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102865639","display_name":"Ji-Ho Cho","orcid":"https://orcid.org/0000-0002-6445-7187"},"institutions":[],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ji-Ho Cho","raw_affiliation_strings":["Airy3D Inc., Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Airy3D Inc., Montreal, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064153426","display_name":"Neeth Kunnath","orcid":null},"institutions":[],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Neeth Kunnath","raw_affiliation_strings":["Airy3D Inc., Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Airy3D Inc., Montreal, Canada","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":0,"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":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":null,"issue":null,"first_page":"109","last_page":"116"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9999,"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":0.9999,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9987,"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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9974,"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/benchmark","display_name":"Benchmark (surveying)","score":0.6944937}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73435044},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7262927},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6944937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.67317736},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5653878},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5300619},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5161139},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.51171327},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.46392617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45996696},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.449273},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/crv50864.2020.00023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":37,"referenced_works":["https://openalex.org/W1479814506","https://openalex.org/W1483019628","https://openalex.org/W1509167548","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1903029394","https://openalex.org/W1987648924","https://openalex.org/W2001022596","https://openalex.org/W2021191215","https://openalex.org/W2093500899","https://openalex.org/W2150066425","https://openalex.org/W2153388956","https://openalex.org/W2159203540","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2254462240","https://openalex.org/W2264432461","https://openalex.org/W2503186844","https://openalex.org/W2512689497","https://openalex.org/W2555618208","https://openalex.org/W2613718673","https://openalex.org/W2794739174","https://openalex.org/W2796461436","https://openalex.org/W2805646839","https://openalex.org/W2885093229","https://openalex.org/W2886851716","https://openalex.org/W2963045776","https://openalex.org/W2963316641","https://openalex.org/W2963416674","https://openalex.org/W2963417597","https://openalex.org/W2963867516","https://openalex.org/W2964110533","https://openalex.org/W2964121744","https://openalex.org/W2969202876","https://openalex.org/W2998293366","https://openalex.org/W4206434639","https://openalex.org/W639708223"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4226493464","https://openalex.org/W3173235360","https://openalex.org/W3133861977","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2951211570","https://openalex.org/W2174948646","https://openalex.org/W2091883426","https://openalex.org/W2024017047"],"abstract_inverted_index":{"Irregular":[0],"sparse":[1,31,50,62,104,140],"depth":[2,34,51,75,168,174],"densification":[3,52,169],"has":[4],"attracted":[5],"a":[6,46,143],"significant":[7],"amount":[8],"of":[9,153],"recent":[10],"interests":[11],"in":[12,37,69,177],"computer":[13],"vision,":[14],"robotics,":[15],"autonomous":[16],"driving":[17],"and":[18,32,76,87,180],"augmented":[19],"reality":[20],"applications.":[21],"Low-cost":[22],"3D":[23],"sensors":[24],"available":[25],"on":[26,108,171],"the":[27,54,89,124,157,166,172],"market":[28],"today":[29],"produce":[30],"irregular":[33],"data":[35],"resulting":[36],"sometimes":[38],"inaccurate":[39],"or":[40],"inconsistent":[41],"results.":[42],"This":[43],"paper":[44],"proposes":[45],"novel":[47],"approach":[48],"for":[49],"called":[53],"Multi-scale":[55],"Anisotropic":[56],"Sparse":[57],"Convolutional":[58],"Network":[59],"(MASC-Net).":[60],"Conventional":[61],"convolutional":[63,105],"approaches":[64],"face":[65],"two":[66],"main":[67],"challenges":[68],"deep":[70,133],"neural":[71],"networks:":[72],"1)":[73],"blurry":[74],"fattening":[77],"artifacts":[78],"near":[79],"object":[80],"boundaries":[81],"due":[82],"to":[83,122,136,139,149,155],"isotropic":[84],"validity":[85,90,111,125],"masks,":[86],"2)":[88],"mask":[91,126],"mismatch":[92,127],"problem":[93],"across":[94],"different":[95],"layers.":[96],"To":[97],"address":[98],"these":[99],"problems,":[100],"we":[101],"propose":[102,118],"anisotropic":[103],"layers":[106],"based":[107],"spatially":[109],"varying":[110],"masks":[112],"with":[113],"guidance":[114],"features.":[115],"We":[116],"also":[117],"Validity-Aware":[119],"Modules":[120],"(VAMs)":[121],"resolve":[123],"problem,":[128],"which":[129],"enables":[130],"many":[131],"modern":[132],"learning":[134],"components":[135],"be":[137],"applied":[138],"data.":[141],"Further,":[142],"multi-scale":[144],"completion":[145,175],"module":[146],"is":[147],"proposed":[148],"utilize":[150],"multiple":[151],"scales":[152],"context":[154],"fill":[156],"missing":[158],"information.":[159],"Experimental":[160],"results":[161],"show":[162],"that":[163],"MASC-Net":[164],"outperforms":[165],"state-of-the-art":[167],"methods":[170],"KITTI":[173],"benchmark":[176],"both":[178],"quantitative":[179],"qualitative":[181],"measures.":[182]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3033080619","counts_by_year":[],"updated_date":"2024-12-28T22:35:51.972617","created_date":"2020-06-12"}