{"id":"https://openalex.org/W2890995532","doi":"https://doi.org/10.1145/3240876.3240891","title":"A novel framework for semantic segmentation with generative adversarial network","display_name":"A novel framework for semantic segmentation with generative adversarial network","publication_year":2018,"publication_date":"2018-08-17","ids":{"openalex":"https://openalex.org/W2890995532","doi":"https://doi.org/10.1145/3240876.3240891","mag":"2890995532"},"language":"en","primary_location":{"id":"doi:10.1145/3240876.3240891","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240876.3240891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Internet Multimedia Computing and Service","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/A5002162759","display_name":"Xinming Zhang","orcid":"https://orcid.org/0000-0002-8136-6834"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinming Zhang","raw_affiliation_strings":["Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101936188","display_name":"Xiaobin Zhu","orcid":"https://orcid.org/0000-0003-3021-0546"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobin Zhu","raw_affiliation_strings":["Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026853565","display_name":"Naiguang Zhang","orcid":"https://orcid.org/0000-0002-7057-4443"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naiguang Zhang","raw_affiliation_strings":["Information Technology Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Technology Institute, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108049287","display_name":"Haisheng Li","orcid":"https://orcid.org/0000-0003-4861-0513"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haisheng Li","raw_affiliation_strings":["Beijing Technology and Business University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003131468","display_name":"Qiang Cai","orcid":"https://orcid.org/0000-0002-3865-9252"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Cai","raw_affiliation_strings":["Beijing Technology and Business University Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Technology and Business University Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025384190","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-7383-4167"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Information Technology Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Technology Institute, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5002162759"],"corresponding_institution_ids":["https://openalex.org/I179026463"],"apc_list":null,"apc_paid":null,"fwci":0.1045,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44765679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7840564250946045},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7401244640350342},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6326293349266052},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6171447038650513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6075562834739685},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6009439826011658},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.48430243134498596},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4693492352962494},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4672263562679291},{"id":"https://openalex.org/keywords/contiguity","display_name":"Contiguity","score":0.4581869840621948},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45435819029808044},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4294198155403137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41050103306770325},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40351980924606323}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7840564250946045},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7401244640350342},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6326293349266052},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6171447038650513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6075562834739685},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6009439826011658},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.48430243134498596},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4693492352962494},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4672263562679291},{"id":"https://openalex.org/C68767595","wikidata":"https://www.wikidata.org/wiki/Q1677999","display_name":"Contiguity","level":2,"score":0.4581869840621948},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45435819029808044},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4294198155403137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41050103306770325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40351980924606323},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3240876.3240891","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240876.3240891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Internet Multimedia Computing and Service","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.699999988079071,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1745334888","https://openalex.org/W1849277567","https://openalex.org/W1903029394","https://openalex.org/W2031489346","https://openalex.org/W2037227137","https://openalex.org/W2124592697","https://openalex.org/W2161236525","https://openalex.org/W2286929393","https://openalex.org/W2340897893","https://openalex.org/W2485522583","https://openalex.org/W2508741746","https://openalex.org/W2516063657","https://openalex.org/W2554423077","https://openalex.org/W2630837129","https://openalex.org/W2737312250","https://openalex.org/W2950510876","https://openalex.org/W2952596663","https://openalex.org/W2952865063","https://openalex.org/W2953384591","https://openalex.org/W2963073614","https://openalex.org/W2963108253","https://openalex.org/W2963563573","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W2995777218","https://openalex.org/W3217069185","https://openalex.org/W4308928038","https://openalex.org/W3049340819","https://openalex.org/W4200430540","https://openalex.org/W3141413246","https://openalex.org/W2888032422","https://openalex.org/W4322709305","https://openalex.org/W2808862658","https://openalex.org/W4391899165"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,23,61,119,123],"plays":[2],"an":[3,112],"important":[4],"role":[5],"in":[6,89],"a":[7,55,60,64],"series":[8],"of":[9,17,50,59,85,128,142],"high-level":[10],"computer":[11],"vision":[12],"applications.":[13],"However,":[14],"the":[15,37,45,83,90,95,100,108,118,122,126,140,143],"performance":[16],"Convolutional":[18],"Neural":[19],"Network":[20,67],"(CNN)":[21],"based":[22],"models":[24],"is":[25,69,106],"currently":[26],"influenced":[27],"by":[28,36,76],"higher":[29,130],"order":[30,131],"inconsistencies,":[31],"which":[32],"are":[33],"mainly":[34],"caused":[35],"CNNs":[38],"built-in":[39],"invariance":[40],"to":[41,71,117],"spatial":[42,79],"transformations":[43],"and":[44,63,92],"independent":[46],"prediction":[47],"for":[48],"each":[49],"pixel.":[51],"In":[52],"this":[53,73],"paper,":[54],"novel":[56],"framework,":[57],"consisting":[58],"network":[62],"Generative":[65],"Adversarial":[66],"(GAN),":[68],"proposed":[70,144],"tackle":[72],"challenging":[74],"problem":[75],"enforcing":[77],"long-range":[78],"label":[80],"contiguity.":[81],"With":[82],"help":[84],"fully":[86],"connected":[87],"layers":[88],"discriminator":[91],"adversarial":[93],"training,":[94],"GAN":[96,109],"model":[97,110,124],"can":[98],"evaluate":[99],"higher-order":[101,114],"potentials":[102,115],"loss.":[103],"The":[104],"motivation":[105],"that":[107],"provides":[111],"auxiliary":[113],"loss":[116],"model,":[120],"thus":[121],"have":[125],"ability":[127],"correcting":[129],"inconsistencies.":[132],"Extensive":[133],"experiments":[134],"on":[135],"public":[136],"benchmarking":[137],"database":[138],"demonstrate":[139],"effectiveness":[141],"method.":[145]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}