{"id":"https://openalex.org/W4402915494","doi":"https://doi.org/10.1109/icip51287.2024.10647354","title":"Robust 3D Semantic Segmentation With Incomplete Point Clouds Based on Sequential Frame Sampling","display_name":"Robust 3D Semantic Segmentation With Incomplete Point Clouds Based on Sequential Frame Sampling","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402915494","doi":"https://doi.org/10.1109/icip51287.2024.10647354"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10647354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10647354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","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/A5009394089","display_name":"Masahiro Yamaguchi","orcid":"https://orcid.org/0000-0003-1001-4505"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masahiro Yamaguchi","raw_affiliation_strings":["NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058678583","display_name":"Kyota Higa","orcid":"https://orcid.org/0009-0008-0526-9662"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kyota Higa","raw_affiliation_strings":["NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110507817","display_name":"Toshinori Hosoi","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshinori Hosoi","raw_affiliation_strings":["NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010157078","display_name":"Takashi Shibata","orcid":"https://orcid.org/0000-0001-8072-3847"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi Shibata","raw_affiliation_strings":["NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"NEC Corporation Visual Intelligence Research Laboratories Shimonumabe 1753, Nakahara-ku,Kawasaki,Kanagawa,Japan","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009394089"],"corresponding_institution_ids":["https://openalex.org/I118347220"],"apc_list":null,"apc_paid":null,"fwci":0.8835,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80489401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3526","last_page":"3532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9947999715805054,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.747150719165802},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6371013522148132},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6041293740272522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5780367255210876},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.573714554309845},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5084611177444458},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07183197140693665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.747150719165802},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6371013522148132},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6041293740272522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5780367255210876},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.573714554309845},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5084611177444458},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07183197140693665}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10647354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10647354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1987648924","https://openalex.org/W2009422376","https://openalex.org/W2194775991","https://openalex.org/W2336961836","https://openalex.org/W2471962767","https://openalex.org/W2594519801","https://openalex.org/W2624503621","https://openalex.org/W2963125977","https://openalex.org/W2963231572","https://openalex.org/W2963706542","https://openalex.org/W2991216808","https://openalex.org/W3011788244","https://openalex.org/W3034961469","https://openalex.org/W3172717135","https://openalex.org/W3176973414","https://openalex.org/W4386065742","https://openalex.org/W6791458050","https://openalex.org/W6852181636","https://openalex.org/W6853538038"],"related_works":["https://openalex.org/W4399442168","https://openalex.org/W2058170566","https://openalex.org/W2114282491","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,107],"method":[4,16,68,86,121],"for":[5,42,92,100,127,135],"learning":[6],"3D":[7,24,71],"semantic":[8,57,72],"segmentation":[9,58,73],"robust":[10],"to":[11],"incomplete":[12,44,102,137],"point":[13,20,25,48,63,95,103,130,138],"clouds.":[14,49,64],"Our":[15],"first":[17],"generates":[18],"pseud-incomplete":[19,62],"clouds":[21,26,96,104,131,139],"from":[22],"original":[23,94,129],"by":[27,89,124],"sequential":[28],"frame":[29],"sampling":[30],"that":[31,84,119],"creates":[32],"multiple":[33],"subsets":[34],"considering":[35],"the":[36,47,61,70,93,101,128,136,142,148],"continuity":[37],"of":[38,152],"an":[39,80,115],"RGB-D":[40],"sequence":[41],"reproducing":[43],"areas":[45],"in":[46,155],"It":[50],"then":[51],"simultaneously":[52],"learns":[53],"completion":[54],"networks":[55,59],"and":[56,97,132,150],"with":[60,106,141],"We":[65],"evaluate":[66],"our":[67,85,120],"on":[69,77,112],"task.":[74],"Experimental":[75,110],"results":[76,111,146],"ScanNet":[78],"v2,":[79],"indoor":[81],"environment,":[82,117],"show":[83,118],"improves":[87,122],"mIoU":[88,123],"0.4":[90],"points":[91,99,126,134],"6.3":[98],"compared":[105,140],"conventional":[108,143],"method.":[109,144],"WorkPlace":[113],"Dataset,":[114],"outdoor":[116],"6.5":[125],"11.1":[133],"These":[145],"improve":[147],"safety":[149],"operability":[151],"environmental":[153],"awareness":[154],"applications":[156],"such":[157],"as":[158],"robotics.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}