{"id":"https://openalex.org/W4387914365","doi":"https://doi.org/10.1109/codit58514.2023.10284381","title":"Dataset Genreratoin for Semantic Segmentation from 3D Scanned Data Considering Domain Gap","display_name":"Dataset Genreratoin for Semantic Segmentation from 3D Scanned Data Considering Domain Gap","publication_year":2023,"publication_date":"2023-07-03","ids":{"openalex":"https://openalex.org/W4387914365","doi":"https://doi.org/10.1109/codit58514.2023.10284381"},"language":"en","primary_location":{"id":"doi:10.1109/codit58514.2023.10284381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit58514.2023.10284381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)","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/A5050918343","display_name":"Marin Wada","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Marin Wada","raw_affiliation_strings":["Graduate School of Science and Technology,Dept. of Computer Science","Dept. of Computer Science, Graduate School of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology,Dept. of Computer Science","institution_ids":[]},{"raw_affiliation_string":"Dept. of Computer Science, Graduate School of Science and Technology","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012782866","display_name":"Miho Adachi","orcid":"https://orcid.org/0009-0000-3802-4866"},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Miho Adachi","raw_affiliation_strings":["School of Science and Technology Meiji University,Dept. of Computer Science,Kawasaki,Japan","Dept. of Computer Science, School of Science and Technology Meiji University, Kawasaki, Japan"],"affiliations":[{"raw_affiliation_string":"School of Science and Technology Meiji University,Dept. of Computer Science,Kawasaki,Japan","institution_ids":["https://openalex.org/I16656306"]},{"raw_affiliation_string":"Dept. of Computer Science, School of Science and Technology Meiji University, Kawasaki, Japan","institution_ids":["https://openalex.org/I16656306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013511162","display_name":"Yuriko Ueda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuriko Ueda","raw_affiliation_strings":["Graduate School of Science and Technology,Dept. of Computer Science","Dept. of Computer Science, Graduate School of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology,Dept. of Computer Science","institution_ids":[]},{"raw_affiliation_string":"Dept. of Computer Science, Graduate School of Science and Technology","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035420223","display_name":"Ryusuke Miyamoto","orcid":"https://orcid.org/0000-0001-9450-4493"},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryusuke Miyamoto","raw_affiliation_strings":["School of Science and Technology Meiji University,Dept. of Computer Science,Kawasaki,Japan","Dept. of Computer Science, School of Science and Technology Meiji University, Kawasaki, Japan"],"affiliations":[{"raw_affiliation_string":"School of Science and Technology Meiji University,Dept. of Computer Science,Kawasaki,Japan","institution_ids":["https://openalex.org/I16656306"]},{"raw_affiliation_string":"Dept. of Computer Science, School of Science and Technology Meiji University, Kawasaki, Japan","institution_ids":["https://openalex.org/I16656306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050918343"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6279,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64694735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1711","last_page":"1716"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9986000061035156,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/computer-science","display_name":"Computer science","score":0.8266688585281372},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7518117427825928},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.743012547492981},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6095502376556396},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5749145746231079},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5658191442489624},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.5440279245376587},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4679039418697357},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.4502257704734802},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4459390342235565},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4363091289997101},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4252592921257019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3989606499671936},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2385171353816986},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.10165050625801086}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8266688585281372},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7518117427825928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.743012547492981},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6095502376556396},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5749145746231079},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5658191442489624},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.5440279245376587},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4679039418697357},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.4502257704734802},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4459390342235565},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4363091289997101},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4252592921257019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3989606499671936},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2385171353816986},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.10165050625801086},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/codit58514.2023.10284381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit58514.2023.10284381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2029629075","https://openalex.org/W2094430142","https://openalex.org/W2340897893","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2560023338","https://openalex.org/W2603777577","https://openalex.org/W2953250742","https://openalex.org/W2962689474","https://openalex.org/W2964217532","https://openalex.org/W2971453269","https://openalex.org/W3016452182","https://openalex.org/W3025573667","https://openalex.org/W3114460273","https://openalex.org/W3116392793","https://openalex.org/W3120688681","https://openalex.org/W4292793992","https://openalex.org/W4308831279","https://openalex.org/W6639102338","https://openalex.org/W6756444276","https://openalex.org/W6787877289","https://openalex.org/W6810151623"],"related_works":["https://openalex.org/W3016928466","https://openalex.org/W4389574804","https://openalex.org/W2565795945","https://openalex.org/W2936725271","https://openalex.org/W4239538403","https://openalex.org/W3150655618","https://openalex.org/W3108295644","https://openalex.org/W1578717197","https://openalex.org/W2626737336","https://openalex.org/W2005998065"],"abstract_inverted_index":{"An":[0],"autonomous":[1,36,139],"moving":[2,29,140],"scheme":[3,81],"with":[4,103],"semantic":[5,21],"information":[6],"extracted":[7],"from":[8,57],"images":[9,45,102,113],"captured":[10],"by":[11,124],"the":[12,28,79,84,97,125,132,134,142],"monocular":[13],"camera":[14],"was":[15,122,145],"proposed,":[16],"providing":[17],"accurate":[18],"results":[19,106],"of":[20,44,100,131],"segmentation.":[22],"A":[23],"training":[24],"dataset":[25,42,65],"must":[26],"accommodate":[27],"environment":[30],"to":[31,82,86,95],"train":[32],"a":[33,40],"classifier":[34],"for":[35,61,138],"moving.":[37],"However,":[38],"preparing":[39],"large-scale":[41],"composed":[43],"having":[46],"pixel-wise":[47],"manually-annotated":[48],"class":[49,137],"labels":[50],"is":[51,76],"impractical.":[52],"We":[53],"generated":[54],"datasets":[55],"automatically":[56],"3D":[58,108],"point":[59,109],"clouds,":[60],"reducing":[62],"manpower.":[63],"The":[64,128],"had":[66],"significant":[67,136],"problems:":[68],"domain":[69],"gap":[70,85],"and":[71,111],"shadows.":[72,104],"Therefore,":[73],"style":[74],"transfer":[75],"incorporated":[77],"in":[78],"proposed":[80,126],"bridge":[83],"resolve":[87],"this":[88],"problem.":[89],"Moreover,":[90],"pseudo":[91],"shadows":[92],"were":[93],"added":[94],"improve":[96],"classification":[98,120,129],"accuracy":[99,121,130],"testing":[101,112],"Experimental":[105],"using":[107],"clouds":[110],"taken":[114],"around":[115],"Tsukuba":[116,143],"City":[117],"showed":[118],"that":[119],"improved":[123],"scheme.":[127],"sidewalk,":[133],"most":[135],"at":[141],"Challenge,":[144],"95.7%.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
