{"id":"https://openalex.org/W4283696183","doi":"https://doi.org/10.1109/lra.2022.3183932","title":"BIMS-PU: Bi-Directional and Multi-Scale Point Cloud Upsampling","display_name":"BIMS-PU: Bi-Directional and Multi-Scale Point Cloud Upsampling","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4283696183","doi":"https://doi.org/10.1109/lra.2022.3183932"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2022.3183932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3183932","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.12648","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054798446","display_name":"Yechao Bai","orcid":"https://orcid.org/0000-0001-5114-4192"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yechao Bai","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-5114-4192","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108050045","display_name":"Xiaogang Wang","orcid":"https://orcid.org/0000-0002-7159-1202"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xiaogang Wang","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-7159-1202","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064469965","display_name":"Marcelo H. Ang","orcid":"https://orcid.org/0000-0001-8277-6408"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Marcelo H. Ang Jr","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-8277-6408","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066830185","display_name":"Daniela Rus","orcid":"https://orcid.org/0000-0001-5473-3566"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniela Rus","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5473-3566","affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6987,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.58815911,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"7","issue":"3","first_page":"7447","last_page":"7454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9976999759674072,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.9624868035316467},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7218010425567627},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6786046624183655},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5328182578086853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5222190618515015},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5074600577354431},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47847387194633484},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.44929563999176025},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4456402659416199},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4439057409763336},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3726920485496521},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33942103385925293},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1575407087802887},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10513272881507874},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07511809468269348}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9624868035316467},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7218010425567627},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6786046624183655},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5328182578086853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5222190618515015},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5074600577354431},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47847387194633484},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.44929563999176025},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4456402659416199},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4439057409763336},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3726920485496521},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33942103385925293},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1575407087802887},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10513272881507874},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07511809468269348},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/lra.2022.3183932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3183932","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2206.12648","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.12648","pdf_url":"https://arxiv.org/pdf/2206.12648","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:dspace.mit.edu:1721.1/144058","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/144058","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.12648","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.12648","pdf_url":"https://arxiv.org/pdf/2206.12648","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1920022804","https://openalex.org/W1987985833","https://openalex.org/W2016598597","https://openalex.org/W2160065436","https://openalex.org/W2194775991","https://openalex.org/W2560609797","https://openalex.org/W2560722161","https://openalex.org/W2563685048","https://openalex.org/W2565639579","https://openalex.org/W2594519801","https://openalex.org/W2784398087","https://openalex.org/W2796426482","https://openalex.org/W2806332096","https://openalex.org/W2884154111","https://openalex.org/W2923834406","https://openalex.org/W2963121255","https://openalex.org/W2963158438","https://openalex.org/W2963390820","https://openalex.org/W2963610452","https://openalex.org/W2963680153","https://openalex.org/W2963729050","https://openalex.org/W2963857746","https://openalex.org/W2964253930","https://openalex.org/W2964444661","https://openalex.org/W2979750740","https://openalex.org/W2981440248","https://openalex.org/W2990775046","https://openalex.org/W2997337685","https://openalex.org/W3034971973","https://openalex.org/W3035014292","https://openalex.org/W3106699132","https://openalex.org/W3122633743","https://openalex.org/W3175676582","https://openalex.org/W3184736166","https://openalex.org/W4394652702","https://openalex.org/W6637242042","https://openalex.org/W6640300118","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6788305448"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W3149642877","https://openalex.org/W3215923428","https://openalex.org/W3176213335","https://openalex.org/W4328027016"],"abstract_inverted_index":{"The":[0,117],"learning":[1],"and":[2,95,127,163],"aggregation":[3],"of":[4,35,45,55,61,145,158],"multi-scale":[5,29,118],"features":[6,30,119],"are":[7,120],"essential":[8],"in":[9,19,123],"empowering":[10],"neural":[11],"networks":[12],"to":[13,140,154,176],"capture":[14],"the":[15,20,64,87,101,110,156,195],"fine-grained":[16],"geometric":[17],"details":[18],"point":[21,33,79,143,186],"cloud":[22,34,80,187],"upsampling":[23,62,81,188],"task.":[24],"Most":[25],"existing":[26,49],"approaches":[27],"extract":[28],"from":[31,58],"a":[32,36,42,52,59,77,92,124,130,151],"fixed":[37],"resolution,":[38],"hence":[39],"obtain":[40],"only":[41],"limited":[43],"level":[44],"details.":[46],"Though":[47],"an":[48],"approach":[50],"aggregates":[51],"feature":[53,88,132],"hierarchy":[54],"different":[56,146,167],"resolutions":[57],"cascade":[60],"sub-network,":[63],"training":[65,157],"is":[66,137],"complex":[67],"with":[68,91],"expensive":[69],"computation.":[70],"To":[71],"address":[72],"these":[73],"issues,":[74],"we":[75,99,149,183],"construct":[76],"new":[78],"pipeline":[82],"called":[83],"BIMS-PU":[84],"that":[85,170,185],"integrates":[86],"pyramid":[89],"architecture":[90],"bi-directional":[93],"up":[94],"downsampling":[96],"path.":[97],"Specifically,":[98],"decompose":[100],"up/downsampling":[102,106],"procedure":[103],"into":[104,114],"several":[105],"sub-steps":[107],"by":[108,193],"breaking":[109],"target":[111],"sampling":[112],"factor":[113],"smaller":[115],"factors.":[116],"naturally":[121],"produced":[122],"parallel":[125],"manner":[126],"aggregated":[128],"using":[129],"fast":[131],"fusion":[133],"method.":[134],"Supervision":[135],"signal":[136],"simultaneously":[138],"applied":[139],"all":[141],"upsampled":[142],"clouds":[144],"scales.":[147],"Moreover,":[148],"formulate":[150],"residual":[152],"block":[153],"ease":[155],"our":[159,171],"model.":[160],"Extensive":[161],"quantitative":[162],"qualitative":[164],"experiments":[165],"on":[166],"datasets":[168],"show":[169],"method":[172],"achieves":[173],"superior":[174],"results":[175],"state-of-the-art":[177],"approaches.":[178],"Last":[179],"but":[180],"not":[181],"least,":[182],"demonstrate":[184],"can":[189],"improve":[190],"robot":[191],"perception":[192],"ameliorating":[194],"3D":[196],"data":[197],"quality.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}