{"id":"https://openalex.org/W2780280500","doi":"https://doi.org/10.1109/mmsp.2018.8547096","title":"Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels","display_name":"Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2780280500","doi":"https://doi.org/10.1109/mmsp.2018.8547096","mag":"2780280500"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp.2018.8547096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2018.8547096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)","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/1712.09558","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015331392","display_name":"\u00c7a\u011flar Aytekin","orcid":"https://orcid.org/0000-0003-4041-9757"},"institutions":[{"id":"https://openalex.org/I2738502077","display_name":"Nokia (Finland)","ror":"https://ror.org/04pkc8m17","country_code":"FI","type":"company","lineage":["https://openalex.org/I2738502077"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Caglar Aytekin","raw_affiliation_strings":["Nokia Technologies, Tampere, Finland","Nokia Technologies; Tampere Finland"],"affiliations":[{"raw_affiliation_string":"Nokia Technologies, Tampere, Finland","institution_ids":["https://openalex.org/I2738502077"]},{"raw_affiliation_string":"Nokia Technologies; Tampere Finland","institution_ids":["https://openalex.org/I2738502077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035218967","display_name":"Xingyang Ni","orcid":"https://orcid.org/0000-0002-6438-5179"},"institutions":[{"id":"https://openalex.org/I2738502077","display_name":"Nokia (Finland)","ror":"https://ror.org/04pkc8m17","country_code":"FI","type":"company","lineage":["https://openalex.org/I2738502077"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Xingyang Ni","raw_affiliation_strings":["Nokia Technologies, Tampere, Finland","Nokia Technologies; Tampere Finland"],"affiliations":[{"raw_affiliation_string":"Nokia Technologies, Tampere, Finland","institution_ids":["https://openalex.org/I2738502077"]},{"raw_affiliation_string":"Nokia Technologies; Tampere Finland","institution_ids":["https://openalex.org/I2738502077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049106121","display_name":"Francesco Cricri","orcid":"https://orcid.org/0000-0002-1521-420X"},"institutions":[{"id":"https://openalex.org/I2738502077","display_name":"Nokia (Finland)","ror":"https://ror.org/04pkc8m17","country_code":"FI","type":"company","lineage":["https://openalex.org/I2738502077"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Francesco Cricri","raw_affiliation_strings":["Nokia Technologies, Tampere, Finland","Nokia Technologies; Tampere Finland"],"affiliations":[{"raw_affiliation_string":"Nokia Technologies, Tampere, Finland","institution_ids":["https://openalex.org/I2738502077"]},{"raw_affiliation_string":"Nokia Technologies; Tampere Finland","institution_ids":["https://openalex.org/I2738502077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373580","display_name":"Lixin Fan","orcid":"https://orcid.org/0000-0002-8162-7096"},"institutions":[{"id":"https://openalex.org/I2738502077","display_name":"Nokia (Finland)","ror":"https://ror.org/04pkc8m17","country_code":"FI","type":"company","lineage":["https://openalex.org/I2738502077"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Lixin Fan","raw_affiliation_strings":["Nokia Technologies, Tampere, Finland","Nokia Technologies; Tampere Finland"],"affiliations":[{"raw_affiliation_string":"Nokia Technologies, Tampere, Finland","institution_ids":["https://openalex.org/I2738502077"]},{"raw_affiliation_string":"Nokia Technologies; Tampere Finland","institution_ids":["https://openalex.org/I2738502077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015289739","display_name":"Emre Aksu","orcid":"https://orcid.org/0000-0001-7363-2824"},"institutions":[{"id":"https://openalex.org/I2738502077","display_name":"Nokia (Finland)","ror":"https://ror.org/04pkc8m17","country_code":"FI","type":"company","lineage":["https://openalex.org/I2738502077"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Emre Aksu","raw_affiliation_strings":["Nokia Technologies, Tampere, Finland","Nokia Technologies; Tampere Finland"],"affiliations":[{"raw_affiliation_string":"Nokia Technologies, Tampere, Finland","institution_ids":["https://openalex.org/I2738502077"]},{"raw_affiliation_string":"Nokia Technologies; Tampere Finland","institution_ids":["https://openalex.org/I2738502077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5015331392"],"corresponding_institution_ids":["https://openalex.org/I2738502077"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00469406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"88","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T11094","display_name":"Face Recognition and Perception","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9894000291824341,"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":0.8393582105636597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.759097695350647},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.733780026435852},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6349262595176697},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6298795342445374},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5698907375335693},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5668045282363892},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5317244529724121},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5191335082054138},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4710533320903778},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.447824627161026},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44731295108795166},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4252408742904663},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4232110381126404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8393582105636597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.759097695350647},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.733780026435852},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6349262595176697},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6298795342445374},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5698907375335693},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5668045282363892},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5317244529724121},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5191335082054138},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4710533320903778},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.447824627161026},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44731295108795166},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4252408742904663},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4232110381126404},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/mmsp.2018.8547096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2018.8547096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1712.09558","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1712.09558","pdf_url":"https://arxiv.org/pdf/1712.09558","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":"mag:2780280500","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1712.09558.pdf","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.1712.09558","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1712.09558","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:1712.09558","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1712.09558","pdf_url":"https://arxiv.org/pdf/1712.09558","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":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2780280500.pdf","grobid_xml":"https://content.openalex.org/works/W2780280500.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1841592590","https://openalex.org/W1903029394","https://openalex.org/W1910657905","https://openalex.org/W1942214758","https://openalex.org/W1996326832","https://openalex.org/W2002781701","https://openalex.org/W2037954058","https://openalex.org/W2039684198","https://openalex.org/W2086791339","https://openalex.org/W2121927366","https://openalex.org/W2126526065","https://openalex.org/W2128340050","https://openalex.org/W2137110664","https://openalex.org/W2149233894","https://openalex.org/W2155709634","https://openalex.org/W2161185676","https://openalex.org/W2171378720","https://openalex.org/W2194775991","https://openalex.org/W2209409763","https://openalex.org/W2286929393","https://openalex.org/W2293105860","https://openalex.org/W2293332611","https://openalex.org/W2308827341","https://openalex.org/W2338972621","https://openalex.org/W2461475918","https://openalex.org/W2519528544","https://openalex.org/W2556959001","https://openalex.org/W2949117887","https://openalex.org/W2949341804","https://openalex.org/W2949370174","https://openalex.org/W2950622378","https://openalex.org/W2952865063","https://openalex.org/W2963299740","https://openalex.org/W2963674932","https://openalex.org/W3098389804","https://openalex.org/W4239147634","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6638667902","https://openalex.org/W6638783484","https://openalex.org/W6639359414","https://openalex.org/W6640759395","https://openalex.org/W6684191040","https://openalex.org/W6726799623","https://openalex.org/W6726904149","https://openalex.org/W6749831782","https://openalex.org/W7048528128"],"related_works":["https://openalex.org/W2962774453","https://openalex.org/W2612507721","https://openalex.org/W2954156922","https://openalex.org/W2801031914","https://openalex.org/W2962747122","https://openalex.org/W2917696722","https://openalex.org/W3017327777","https://openalex.org/W3200530022","https://openalex.org/W2914318243","https://openalex.org/W2999921958","https://openalex.org/W2738149063","https://openalex.org/W3111084573","https://openalex.org/W3104282073","https://openalex.org/W2559966999","https://openalex.org/W3156397119","https://openalex.org/W2774231360","https://openalex.org/W2755686789","https://openalex.org/W3203341530","https://openalex.org/W2920913251","https://openalex.org/W3105636206"],"abstract_inverted_index":{"Computer":[0],"vision":[1],"algorithms":[2],"with":[3,22,153],"pixel-wise":[4],"labeling":[5],"tasks,":[6],"such":[7,53,178,189],"as":[8,190],"semantic":[9],"segmentation":[10,29],"and":[11,33,101,161,165,193],"salient":[12,62,84,143,157],"object":[13,63,85,99,144,158],"detection,":[14],"have":[15,38,52],"gone":[16],"through":[17],"a":[18,70,74,129,163,166,179],"significant":[19],"accuracy":[20,152],"increase":[21],"the":[23,49,58,98,102,136,154],"incorporation":[24],"of":[25,40,42,61,105,135,138],"deep":[26,142,156],"learning.":[27],"Deep":[28],"methods":[30,160],"slightly":[31],"modify":[32],"fine-tune":[34],"pre-trained":[35],"networks":[36,56,116,146],"that":[37,95,117,140],"hundreds":[39],"millions":[41],"parameters.":[43],"In":[44],"this":[45,66],"work,":[46],"we":[47,68,127],"question":[48],"need":[50],"to":[51,72,92,112,171,174],"memory":[54,186],"demanding":[55],"for":[57,183],"specific":[59],"task":[60],"segmentation.":[64],"To":[65],"end,":[67],"propose":[69],"way":[71],"learn":[73],"memory-efficient":[75,130,169],"network":[76,131,180],"from":[77],"scratch":[78],"by":[79],"training":[80],"it":[81],"only":[82,133],"on":[83,119],"detection":[86,145,159],"datasets.":[87],"Our":[88,148],"method":[89,149],"encodes":[90],"images":[91],"gridized":[93],"superpixels":[94],"preserve":[96],"both":[97],"boundaries":[100],"connectivity":[103],"rules":[104],"regular":[106,120],"pixels.":[107],"This":[108],"representation":[109],"allows":[110],"us":[111],"use":[113],"convolutional":[114],"neural":[115],"operate":[118],"grids.":[121],"By":[122],"using":[123,132],"these":[124],"encoded":[125],"images,":[126],"train":[128],"0.048\\%":[134],"number":[137],"parameters":[139],"other":[141],"have.":[147],"shows":[150],"comparable":[151],"state-of-the-art":[155],"provides":[162],"faster":[164],"much":[167],"more":[168],"alternative":[170],"them.":[172],"Due":[173],"its":[175],"easy":[176],"deployment,":[177],"is":[181],"preferable":[182],"applications":[184],"in":[185],"limited":[187],"devices":[188],"mobile":[191],"phones":[192],"IoT":[194],"devices.":[195]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
