{"id":"https://openalex.org/W2745995939","doi":"https://doi.org/10.1109/cvpr.2018.00309","title":"Tags2Parts: Discovering Semantic Regions from Shape Tags","display_name":"Tags2Parts: Discovering Semantic Regions from Shape Tags","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2745995939","doi":"https://doi.org/10.1109/cvpr.2018.00309","mag":"2745995939"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2018.00309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.06673","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109431903","display_name":"Sanjeev Muralikrishnan","orcid":"https://orcid.org/0000-0002-3556-5007"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]},{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["IN","US"],"is_corresponding":true,"raw_author_name":"Sanjeev Muralikrishnan","raw_affiliation_strings":["IIT Bombay","Adobe Systems (United States), San Jose, United States"],"affiliations":[{"raw_affiliation_string":"IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Adobe Systems (United States), San Jose, United States","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041004771","display_name":"Vladimir G. Kim","orcid":"https://orcid.org/0000-0002-3996-6588"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]},{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Vladimir G. Kim","raw_affiliation_strings":["IIT Bombay","Adobe Systems (United States), San Jose, United States"],"affiliations":[{"raw_affiliation_string":"IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Adobe Systems (United States), San Jose, United States","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108481672","display_name":"Siddhartha Chaudhuri","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Siddhartha Chaudhuri","raw_affiliation_strings":["IIT Bombay","Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109431903"],"corresponding_institution_ids":["https://openalex.org/I1306409833","https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":0.2077,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47068528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"26","issue":null,"first_page":"2926","last_page":"2935"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9993000030517578,"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":0.9993000030517578,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9945999979972839,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9918000102043152,"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":0.8070218563079834},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7356898784637451},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6734498739242554},{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.6535198092460632},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6177711486816406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5839781165122986},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5630492568016052},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5469220280647278},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35193008184432983},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33377885818481445},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3221972584724426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8070218563079834},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7356898784637451},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6734498739242554},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.6535198092460632},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6177711486816406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5839781165122986},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5630492568016052},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5469220280647278},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35193008184432983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33377885818481445},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3221972584724426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cvpr.2018.00309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1708.06673","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.06673","pdf_url":"https://arxiv.org/pdf/1708.06673","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":"","raw_type":"text"},{"id":"mag:2745995939","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1708.06673","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1708.06673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1708.06673","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.06673","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.06673","pdf_url":"https://arxiv.org/pdf/1708.06673","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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2745995939.pdf","grobid_xml":"https://content.openalex.org/works/W2745995939.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W318792885","https://openalex.org/W1569512051","https://openalex.org/W1783315696","https://openalex.org/W1901129140","https://openalex.org/W1920022804","https://openalex.org/W1994488211","https://openalex.org/W2003940193","https://openalex.org/W2029524207","https://openalex.org/W2063513338","https://openalex.org/W2097117768","https://openalex.org/W2106210044","https://openalex.org/W2106723645","https://openalex.org/W2133324800","https://openalex.org/W2165308258","https://openalex.org/W2190691619","https://openalex.org/W2553307952","https://openalex.org/W2556802233","https://openalex.org/W2560609797","https://openalex.org/W2565662353","https://openalex.org/W2610837079","https://openalex.org/W2724314443","https://openalex.org/W2737081152","https://openalex.org/W2737234477","https://openalex.org/W2765731028","https://openalex.org/W2950762923","https://openalex.org/W2952072685","https://openalex.org/W2962851944","https://openalex.org/W3004739592","https://openalex.org/W3100955000","https://openalex.org/W3104141662","https://openalex.org/W4251944521","https://openalex.org/W6611089629","https://openalex.org/W6639824700","https://openalex.org/W6640300118","https://openalex.org/W6675392924","https://openalex.org/W6685133223","https://openalex.org/W6697925102","https://openalex.org/W6763422710"],"related_works":["https://openalex.org/W2770949838","https://openalex.org/W3048857148","https://openalex.org/W3044881747","https://openalex.org/W2900234507","https://openalex.org/W2114227971","https://openalex.org/W2951081618","https://openalex.org/W2916686682","https://openalex.org/W2982631194","https://openalex.org/W2773708732","https://openalex.org/W3048112677","https://openalex.org/W2295647632","https://openalex.org/W3137532436","https://openalex.org/W3145199835","https://openalex.org/W2940581368","https://openalex.org/W3033270690","https://openalex.org/W2550475090","https://openalex.org/W2910424828","https://openalex.org/W2552369821","https://openalex.org/W2787287818","https://openalex.org/W3116802826"],"abstract_inverted_index":{"We":[0,106,168],"propose":[1],"a":[2,18,56,152],"novel":[3,57],"method":[4,125,171],"for":[5,144],"discovering":[6],"shape":[7,122,134],"regions":[8,36],"that":[9,61,115],"strongly":[10,164],"correlate":[11],"with":[12,64,93,117,174],"user-prescribed":[13],"tags.":[14],"For":[15],"example,":[16],"given":[17],"collection":[19],"of":[20,120],"chairs":[21],"tagged,":[22],"as":[23,37],"either":[24],"\"has":[25],"armrest\"":[26],"or":[27],"\"lacks":[28],"armrest\",":[29],"our":[30,108,124,154,170],"system":[31],"correctly":[32],"highlights":[33],"the":[34,38,43,77,102,139,146],"armrest":[35],"main":[39],"distinctive":[40],"parts":[41],"between":[42],"two":[44],"chair":[45],"types.":[46],"To":[47],"obtain":[48],"point-wise":[49],"predictions":[50],"from":[51],"shape-wise":[52],"tags":[53],"we":[54,86],"develop":[55],"neural":[58],"network":[59,80],"architecture":[60,104,155],"is":[62,69,81,148,156],"trained":[63],"tag":[65,147],"classification":[66],"loss,":[67],"but":[68,85],"designed":[70],"to":[71,75],"rely":[72],"on":[73,110,165],"segmentation":[74,111],"predict":[76],"tag.":[78],"Our":[79],"inspired":[82],"by":[83],"U-Net,":[84],"replicate":[87],"shallow":[88],"U":[89],"structures":[90],"several":[91,183],"times":[92],"new":[94],"skip":[95],"connections":[96],"and":[97,100,113,162,178,181],"pooling":[98],"layers,":[99],"call":[101],"resulting":[103],"WU-Net.":[105],"test":[107],"method,":[109],"benchmarks":[112],"show":[114],"even":[116],"weak":[118],"supervision":[119,161],"whole":[121],"tags,":[123],"can":[126,141],"infer":[127],"meaningful":[128],"semantic":[129],"regions,":[130],"without":[131],"ever":[132],"observing":[133],"segmentations.":[135],"Further,":[136],"once":[137],"trained,":[138],"model":[140],"process":[142],"shapes":[143],"which":[145],"entirely":[149],"unknown.":[150],"As":[151],"bonus,":[153],"directly":[157],"operational":[158],"under":[159],"full":[160],"performs":[163],"standard":[166],"benchmarks.":[167],"validate":[169],"through":[172],"experiments":[173],"many":[175],"variant":[176],"architectures":[177],"prior":[179],"baselines,":[180],"demonstrate":[182],"applications.":[184]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
