{"id":"https://openalex.org/W2008106311","doi":"https://doi.org/10.1109/icme.2013.6607512","title":"A benchmark for semantic image segmentation","display_name":"A benchmark for semantic image segmentation","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2008106311","doi":"https://doi.org/10.1109/icme.2013.6607512","mag":"2008106311"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2013.6607512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2013.6607512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100658729","display_name":"Hui Li","orcid":"https://orcid.org/0000-0003-0610-1083"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Hui Li","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Tech. Univ., Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Tech. Univ., Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100635804","display_name":"Jianfei Cai","orcid":"https://orcid.org/0000-0002-9444-3763"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jianfei Cai","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Tech. Univ., Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Tech. Univ., Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017373805","display_name":"Thi Nhat Anh Nguyen","orcid":"https://orcid.org/0000-0003-1117-4770"},"institutions":[{"id":"https://openalex.org/I3129492623","display_name":"University of Da Nang","ror":"https://ror.org/03ecpp171","country_code":"VN","type":"education","lineage":["https://openalex.org/I3129492623"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Thi Nhat Anh Nguyen","raw_affiliation_strings":["Danang University of Technology, Vietnam","Danang University of Technology, Danang, Vietnam#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Danang University of Technology, Vietnam","institution_ids":["https://openalex.org/I3129492623"]},{"raw_affiliation_string":"Danang University of Technology, Danang, Vietnam#TAB#","institution_ids":["https://openalex.org/I3129492623"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039953512","display_name":"Jianmin Zheng","orcid":"https://orcid.org/0000-0002-5062-6226"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jianmin Zheng","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Tech. Univ., Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Tech. Univ., Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0787,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.90161582,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9990000128746033,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9990000128746033,"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/T10036","display_name":"Advanced Neural Network 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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9979000091552734,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8294484615325928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7854489088058472},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7835736274719238},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.7675312757492065},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.694434404373169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6325178146362305},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6164504885673523},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6148416996002197},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.5821175575256348},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5075920820236206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44308099150657654},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4263906478881836},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4104832410812378},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37637487053871155},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3354945778846741},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32175734639167786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1088595986366272}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8294484615325928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7854489088058472},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7835736274719238},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.7675312757492065},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.694434404373169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6325178146362305},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6164504885673523},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6148416996002197},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.5821175575256348},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5075920820236206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44308099150657654},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4263906478881836},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4104832410812378},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37637487053871155},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3354945778846741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32175734639167786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1088595986366272},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2013.6607512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2013.6607512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo (ICME)","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":14,"referenced_works":["https://openalex.org/W1785730614","https://openalex.org/W1964884769","https://openalex.org/W1967268147","https://openalex.org/W2037227137","https://openalex.org/W2093164524","https://openalex.org/W2100900426","https://openalex.org/W2119823327","https://openalex.org/W2121927366","https://openalex.org/W2125378844","https://openalex.org/W2134839354","https://openalex.org/W2154791445","https://openalex.org/W2172230297","https://openalex.org/W2186094539","https://openalex.org/W6638212498"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571","https://openalex.org/W2372421320","https://openalex.org/W2551987074"],"abstract_inverted_index":{"Though":[0],"quite":[1],"a":[2,25,29,62,79],"few":[3],"image":[4,18,113],"segmentation":[5,54],"benchmark":[6,15,26],"datasets":[7],"have":[8],"been":[9],"constructed,":[10],"there":[11],"is":[12,84,107],"no":[13],"suitable":[14,109],"for":[16,27,56,67,72,110],"semantic":[17,112],"segmentation.":[19,75],"In":[20],"this":[21],"paper,":[22],"we":[23,77],"construct":[24],"such":[28],"purpose,":[30],"where":[31],"the":[32,38,70,103,116,122],"ground-truths":[33,42],"are":[34],"generated":[35,104],"by":[36],"leveraging":[37],"existing":[39],"fine":[40],"granular":[41],"in":[43],"Berkeley":[44],"Segmentation":[45],"Dataset":[46],"(BSD)":[47],"as":[48,50],"well":[49],"using":[51],"an":[52],"interactive":[53],"tool":[55],"new":[57,80],"images.":[58],"We":[59],"also":[60],"propose":[61,78],"percept-tree-based":[63],"region":[64],"merging":[65],"strategy":[66],"dynamically":[68],"adapting":[69],"ground-truth":[71,105],"evaluating":[73,111],"test":[74],"Moreover,":[76],"evaluation":[81,124],"metric":[82,125],"that":[83,121],"easy":[85],"to":[86],"understand":[87],"and":[88,90,115],"compute,":[89],"does":[91],"not":[92],"require":[93],"boundary":[94],"matching.":[95],"Experimental":[96],"results":[97],"show":[98],"that,":[99],"compared":[100],"with":[101],"BSD,":[102],"dataset":[106],"more":[108],"segmentation,":[114],"conducted":[117],"user":[118,127],"study":[119],"demonstrates":[120],"proposed":[123],"matches":[126],"ranking":[128],"very":[129],"well.":[130]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}