{"id":"https://openalex.org/W4402352158","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651371","title":"MetaMask: Improving Few-Shot Semantic Segmentation via Multi-Mask Calibriation","display_name":"MetaMask: Improving Few-Shot Semantic Segmentation via Multi-Mask Calibriation","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352158","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651371"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651371","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5107079555","display_name":"Li Dinghang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Dinghang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School,China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020361550","display_name":"Zongqing Lu","orcid":"https://orcid.org/0000-0002-1191-9069"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongqing Lu","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School,China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068363216","display_name":"Weiliang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiliang Zheng","raw_affiliation_strings":["Shenzhen Institute of Information Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Information Technology,China","institution_ids":["https://openalex.org/I158809036"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009239895","display_name":"Qingmin Liao","orcid":"https://orcid.org/0000-0002-7509-3964"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingmin Liao","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School,China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101573269","display_name":"Fan Lyu","orcid":"https://orcid.org/0000-0002-0878-5485"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Lyu","raw_affiliation_strings":["CASIA,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CASIA,China","institution_ids":["https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2187,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49996346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9988999962806702,"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":0.7636693716049194},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.7065631151199341},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6488195657730103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5148636102676392},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4750778079032898},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43197938799858093},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34195923805236816},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.13062456250190735}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7636693716049194},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.7065631151199341},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6488195657730103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5148636102676392},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4750778079032898},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43197938799858093},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34195923805236816},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.13062456250190735},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651371","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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":42,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W2037227137","https://openalex.org/W2058715873","https://openalex.org/W2118246710","https://openalex.org/W2145680191","https://openalex.org/W2194775991","https://openalex.org/W2222512263","https://openalex.org/W2412782625","https://openalex.org/W2474531669","https://openalex.org/W2893918048","https://openalex.org/W2908510526","https://openalex.org/W2963078159","https://openalex.org/W2990230185","https://openalex.org/W3033502887","https://openalex.org/W3034552520","https://openalex.org/W3034985049","https://openalex.org/W3047258141","https://openalex.org/W3096609285","https://openalex.org/W3128661784","https://openalex.org/W3157653192","https://openalex.org/W3176065502","https://openalex.org/W3213165621","https://openalex.org/W3214418393","https://openalex.org/W3215041655","https://openalex.org/W4214573368","https://openalex.org/W4214660208","https://openalex.org/W4221153269","https://openalex.org/W4224860128","https://openalex.org/W4287551479","https://openalex.org/W4287755086","https://openalex.org/W4312592495","https://openalex.org/W4312815172","https://openalex.org/W4313196086","https://openalex.org/W4313533477","https://openalex.org/W4319300026","https://openalex.org/W4385245566","https://openalex.org/W4386066138","https://openalex.org/W4386075956","https://openalex.org/W6754568377","https://openalex.org/W6757817989","https://openalex.org/W6778102432"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4298312966","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Few-shot":[0],"Semantic":[1],"Segmentation":[2],"(FSS)":[3],"aims":[4],"to":[5,40,112],"develop":[6],"models":[7],"that":[8],"can":[9],"segment":[10],"previously":[11],"unseen":[12,63,97,118],"classes":[13,64],"with":[14,134],"only":[15],"a":[16,22,66,80,88,135,179],"few":[17],"annotations.":[18],"Recent":[19],"approaches":[20],"employ":[21],"\"multi-mask\"":[23],"framework,":[24],"which":[25,95],"initially":[26],"generates":[27],"various":[28],"mask":[29,38,60,68,101,114],"proposals":[30,39,61],"from":[31],"query":[32,105],"images":[33],"and":[34,65,162,176,188],"then":[35],"matches":[36],"related":[37],"get":[41],"the":[42,57,123,183],"final":[43],"output":[44],"guided":[45],"by":[46,56,174],"support":[47],"images.":[48],"Despite":[49],"its":[50],"promise,":[51],"this":[52,76],"framework":[53],"is":[54,110],"limited":[55],"quality":[58],"of":[59],"for":[62,104,116],"naive":[67],"matching":[69],"process.":[70],"To":[71],"address":[72],"such":[73],"limitations,":[74],"in":[75],"paper,":[77],"we":[78],"propose":[79],"meta-learning-based":[81],"method":[82,146],"called":[83],"MetaMask.":[84],"First,":[85],"MetaMask":[86,121],"builds":[87],"Support-Guided":[89],"Latent":[90],"Object":[91],"Segmenter":[92],"(SG-LOS)":[93],"module,":[94],"incorporates":[96],"class":[98],"information":[99],"into":[100],"proposal":[102],"generation":[103,115],"images,":[106],"where":[107],"episodic":[108],"training":[109],"used":[111],"enhance":[113],"latent":[117],"classes.":[119],"Second,":[120],"improves":[122],"mask-matching":[124],"mechanism":[125],"through":[126],"our":[127,172],"proposed":[128],"Contrastive":[129],"Mask":[130],"Matching":[131],"(CMM)":[132],"module":[133],"cross-image":[136],"multi-level":[137],"contrastive":[138],"learning":[139],"strategy,":[140],"bolstering":[141],"feature":[142],"embedding":[143],"spaces.":[144],"Our":[145],"shows":[147],"competitive":[148],"results":[149],"on":[150,156,182],"two":[151],"main":[152],"benchmarks:":[153],"69.9%":[154],"mIoU":[155,164],"Pascal-5<sup":[157,185],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[158,166,186,190],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i</sup>":[159,167,187,191],"one-shot":[160,168],"setting":[161,178],"49.6%":[163],"COCO-20<sup":[165,189],"setting,":[169],"marginally":[170],"outperforming":[171],"baseline":[173],"6.6%":[175],"5.4%,":[177],"new":[180],"state-of-the-art":[181],"both":[184],"datasets.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}