{"id":"https://openalex.org/W4285102307","doi":"https://doi.org/10.1109/icra46639.2022.9811816","title":"Object Insertion Based Data Augmentation for Semantic Segmentation","display_name":"Object Insertion Based Data Augmentation for Semantic Segmentation","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W4285102307","doi":"https://doi.org/10.1109/icra46639.2022.9811816"},"language":"en","primary_location":{"id":"doi:10.1109/icra46639.2022.9811816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9811816","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5012431195","display_name":"Yuan Ren","orcid":"https://orcid.org/0000-0002-4901-3596"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Yuan Ren","raw_affiliation_strings":["Huawei Noah&#x0027;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x0027;s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694825","display_name":"Siyan Zhao","orcid":"https://orcid.org/0000-0002-5282-3194"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Siyan Zhao","raw_affiliation_strings":["Huawei Noah&#x0027;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x0027;s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"last","author":{"id":null,"display_name":"Liu Bingbing","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Liu Bingbing","raw_affiliation_strings":["Huawei Noah&#x0027;s Ark Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x0027;s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210159102"],"apc_list":null,"apc_paid":null,"fwci":2.6431,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.93975738,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"359","last_page":"365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9965999722480774,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.7799869775772095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6022315621376038},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5855668783187866},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5706697106361389},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4854627251625061},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4258568286895752}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7799869775772095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6022315621376038},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5855668783187866},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5706697106361389},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4854627251625061},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4258568286895752}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra46639.2022.9811816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9811816","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Robotics and Automation (ICRA)","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":41,"referenced_works":["https://openalex.org/W2103018059","https://openalex.org/W2743627947","https://openalex.org/W2794022343","https://openalex.org/W2894931878","https://openalex.org/W2897529137","https://openalex.org/W2898091194","https://openalex.org/W2928716465","https://openalex.org/W2949708697","https://openalex.org/W2954996726","https://openalex.org/W2962843773","https://openalex.org/W2962912109","https://openalex.org/W2963942586","https://openalex.org/W2968296999","https://openalex.org/W2990613095","https://openalex.org/W3003437478","https://openalex.org/W3034314779","https://openalex.org/W3035574168","https://openalex.org/W3035617611","https://openalex.org/W3047223011","https://openalex.org/W3120926185","https://openalex.org/W3136022415","https://openalex.org/W3167095230","https://openalex.org/W3174527233","https://openalex.org/W3176659256","https://openalex.org/W3177330511","https://openalex.org/W3181190968","https://openalex.org/W3183784042","https://openalex.org/W3206724875","https://openalex.org/W3207707490","https://openalex.org/W4309297136","https://openalex.org/W6741441694","https://openalex.org/W6754935415","https://openalex.org/W6755837410","https://openalex.org/W6761035977","https://openalex.org/W6780257433","https://openalex.org/W6781274669","https://openalex.org/W6781919949","https://openalex.org/W6785543708","https://openalex.org/W6786777035","https://openalex.org/W6787112770","https://openalex.org/W6795320955"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Neural":[0],"network":[1,133],"used":[2],"for":[3,15],"the":[4,10,26,56,76,87,101,105,127,130,143,154,160,163,173,182,188],"LiDAR":[5,60,80,145,155,175],"semantic":[6,131,192],"segmentation":[7,132,193],"task":[8],"needs":[9],"point-wise":[11],"labeled":[12,144],"point":[13,146,156],"clouds":[14,157],"training,":[16],"which":[17,124],"is":[18,34,54,71,139],"more":[19],"expensive":[20],"than":[21],"bounding":[22],"box":[23],"annotations.":[24],"Enhancing":[25],"diversity":[27],"of":[28,86,108,129,190],"training":[29],"data":[30,121],"through":[31],"object":[32,44,118,137],"insertion":[33,45,119],"an":[35,117,136],"effective":[36],"method":[37,92,123,185],"to":[38,65,82,113,172],"reduce":[39],"labeling":[40],"costs.":[41],"The":[42,177],"existing":[43],"methods":[46],"are":[47,111,151,169],"mainly":[48],"divided":[49],"into":[50,75,153],"two":[51],"categories.":[52],"First":[53],"\u201ccopy\u201d":[55],"clusters":[57],"from":[58],"a":[59],"frame":[61],"and":[62,98,100,167],"\u201cpaste\u201d":[63],"it":[64],"other":[66],"frames":[67],"or":[68],"positions.":[69],"Second":[70],"inserting":[72],"CAD":[73,89,102,106],"models":[74,107],"background":[77],"then":[78],"using":[79,142],"simulator":[81],"generate":[83,94],"laser":[84],"points":[85],"inserted":[88,152],"models.":[90],"\u201cCopy-paste\u201d":[91],"cannot":[93],"realistic":[95,164],"scanning":[96,165],"lines":[97,166],"shadows,":[99],"models,":[103],"especially":[104],"flexible":[109],"objects,":[110],"hard":[112],"obtain.":[114],"We":[115],"propose":[116],"based":[120],"augmentation":[122,184],"can":[125,186],"increase":[126,187],"performance":[128,189],"remarkably.":[134,195],"First,":[135],"library":[138],"created":[140],"by":[141],"clouds.":[147],"Then,":[148],"these":[149],"objects":[150],"dynamically":[158],"during":[159],"training.":[161],"Finally,":[162],"shadows":[168],"simulated":[170],"according":[171],"real":[174],"parameters.":[176],"experimental":[178],"results":[179],"show":[180],"that":[181],"proposed":[183],"different":[191],"frameworks":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
