{"id":"https://openalex.org/W2884530474","doi":"https://doi.org/10.1109/tcsvt.2018.2859773","title":"Weakly Supervised Salient Object Detection With Spatiotemporal Cascade Neural Networks","display_name":"Weakly Supervised Salient Object Detection With Spatiotemporal Cascade Neural Networks","publication_year":2018,"publication_date":"2018-07-25","ids":{"openalex":"https://openalex.org/W2884530474","doi":"https://doi.org/10.1109/tcsvt.2018.2859773","mag":"2884530474"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2018.2859773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2018.2859773","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pureadmin.qub.ac.uk/ws/files/161711058/2018_TCSVT.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024267153","display_name":"Yi Tang","orcid":"https://orcid.org/0000-0002-4882-5234"},"institutions":[{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Tang","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I4210142539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035616324","display_name":"Wenbin Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Zou","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I4210142539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039127802","display_name":"Zhi Jin","orcid":"https://orcid.org/0000-0001-9670-7366"},"institutions":[{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Jin","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I4210142539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083649562","display_name":"Yuhuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhuan Chen","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I4210142539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016123060","display_name":"Hua Yang","orcid":"https://orcid.org/0000-0001-5536-503X"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yang Hua","raw_affiliation_strings":["EEECS/ECIT, Queen\u2019s University Belfast, Belfast, U.K","EEECS/ECIT, Queen's University Belfast, Belfast, U.K"],"affiliations":[{"raw_affiliation_string":"EEECS/ECIT, Queen\u2019s University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]},{"raw_affiliation_string":"EEECS/ECIT, Queen's University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445591","display_name":"Xia Li","orcid":"https://orcid.org/0000-0002-8043-9966"},"institutions":[{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Li","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China","institution_ids":["https://openalex.org/I4210142539"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5024267153"],"corresponding_institution_ids":["https://openalex.org/I4210142539"],"apc_list":null,"apc_paid":null,"fwci":4.5686,"has_fulltext":true,"cited_by_count":95,"citation_normalized_percentile":{"value":0.96231232,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"29","issue":"7","first_page":"1973","last_page":"1984"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9883999824523926,"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/cascade","display_name":"Cascade","score":0.682051956653595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6803337931632996},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.658970832824707},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6154063940048218},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5592451691627502},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5499125719070435},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.49269750714302063},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42515021562576294},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39706432819366455}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.682051956653595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6803337931632996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.658970832824707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6154063940048218},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5592451691627502},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5499125719070435},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.49269750714302063},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42515021562576294},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39706432819366455},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcsvt.2018.2859773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2018.2859773","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:openaire/7b4601b0-a725-4f90-bcd2-06ab5a45d4aa","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/7b4601b0-a725-4f90-bcd2-06ab5a45d4aa","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/161711058/2018_TCSVT.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Tang, Y, Zou, W, Jin, Z, Chen, Y, Hua, Y & Li, X 2018, 'Weakly Supervised Salient Object Detection with Spatiotemporal Cascade Neural Networks', IEEE Transactions on Circuits and Systems for Video Technology. https://doi.org/10.1109/TCSVT.2018.2859773","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.qub.ac.uk/portal:openaire/7b4601b0-a725-4f90-bcd2-06ab5a45d4aa","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/7b4601b0-a725-4f90-bcd2-06ab5a45d4aa","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/161711058/2018_TCSVT.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Tang, Y, Zou, W, Jin, Z, Chen, Y, Hua, Y & Li, X 2018, 'Weakly Supervised Salient Object Detection with Spatiotemporal Cascade Neural Networks', IEEE Transactions on Circuits and Systems for Video Technology. https://doi.org/10.1109/TCSVT.2018.2859773","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1023919524","display_name":null,"funder_award_id":", Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2956569796","display_name":null,"funder_award_id":"2017032","funder_id":"https://openalex.org/F4320325571","funder_display_name":"Shenzhen University"},{"id":"https://openalex.org/G2981938667","display_name":null,"funder_award_id":"Shenzhen","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3338363611","display_name":null,"funder_award_id":"61872429","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3757194791","display_name":null,"funder_award_id":"JCYJ20","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3866723802","display_name":null,"funder_award_id":"201703","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4246372239","display_name":null,"funder_award_id":"61871273","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5641397543","display_name":null,"funder_award_id":"201708","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6495957267","display_name":null,"funder_award_id":"61701313","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7922070115","display_name":null,"funder_award_id":"61472257","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8263721069","display_name":null,"funder_award_id":"61771321","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G852339338","display_name":null,"funder_award_id":"2017032","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325571","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2884530474.pdf","grobid_xml":"https://content.openalex.org/works/W2884530474.grobid-xml"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W1496571393","https://openalex.org/W1686810756","https://openalex.org/W1783315696","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1942214758","https://openalex.org/W1947031653","https://openalex.org/W1954128991","https://openalex.org/W1965301399","https://openalex.org/W1970800786","https://openalex.org/W1982075130","https://openalex.org/W1985316921","https://openalex.org/W1992992668","https://openalex.org/W1994488211","https://openalex.org/W1996326832","https://openalex.org/W1999478155","https://openalex.org/W2034436892","https://openalex.org/W2036691646","https://openalex.org/W2047670868","https://openalex.org/W2055611119","https://openalex.org/W2056935845","https://openalex.org/W2097117768","https://openalex.org/W2104102555","https://openalex.org/W2105454024","https://openalex.org/W2110019070","https://openalex.org/W2117539524","https://openalex.org/W2126164636","https://openalex.org/W2130637418","https://openalex.org/W2133324800","https://openalex.org/W2133589685","https://openalex.org/W2138682569","https://openalex.org/W2147347517","https://openalex.org/W2155302366","https://openalex.org/W2155893237","https://openalex.org/W2161236525","https://openalex.org/W2164720308","https://openalex.org/W2187281534","https://openalex.org/W2213123247","https://openalex.org/W2293332611","https://openalex.org/W2442791716","https://openalex.org/W2461475918","https://openalex.org/W2470139095","https://openalex.org/W2474876375","https://openalex.org/W2507697802","https://openalex.org/W2518599539","https://openalex.org/W2519528544","https://openalex.org/W2555058893","https://openalex.org/W2560474170","https://openalex.org/W2572591920","https://openalex.org/W2585521554","https://openalex.org/W2588503511","https://openalex.org/W2601074629","https://openalex.org/W2689607630","https://openalex.org/W2740667773","https://openalex.org/W2757028014","https://openalex.org/W2892946444","https://openalex.org/W2949652892","https://openalex.org/W2952793010","https://openalex.org/W2963032190","https://openalex.org/W2963064675","https://openalex.org/W2963603913","https://openalex.org/W2963906836","https://openalex.org/W2964211037","https://openalex.org/W3103757879","https://openalex.org/W6629607343","https://openalex.org/W6675628854","https://openalex.org/W6679384166","https://openalex.org/W6686999899","https://openalex.org/W6735400639","https://openalex.org/W6755407776"],"related_works":["https://openalex.org/W2153719181","https://openalex.org/W1971748923","https://openalex.org/W1566155057","https://openalex.org/W2060986072","https://openalex.org/W2052574922","https://openalex.org/W64588465","https://openalex.org/W3120641340","https://openalex.org/W2117825986","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,29,54],"learning":[2,30],"techniques":[3],"have":[4],"substantially":[5,163],"boosted":[6],"the":[7,17,39,52,65,126,137,149,156,165],"performance":[8],"of":[9,41,91],"salient":[10,18,66,167],"object":[11,19,67,168],"detection":[12,20,68,169],"in":[13,21,69,100,116],"still":[14],"images.":[15],"However,":[16],"videos":[22],"by":[23,80],"using":[24,81],"traditional":[25],"handcrafted":[26],"features":[27,31],"or":[28],"is":[32,145],"not":[33],"fully":[34,119],"investigated,":[35],"probably":[36],"due":[37],"to":[38,64,124,135],"lack":[40],"sufficient":[42],"manually":[43,84],"labeled":[44,85,93],"video":[45,139],"data":[46,86,94,153],"for":[47,51,113],"saliency":[48,77,114,128,140],"modeling,":[49,115],"especially":[50],"data-driven":[53],"learning.":[55],"This":[56],"paper":[57],"proposes":[58],"a":[59,70,75,88,101,107],"novel":[60],"weakly":[61,92],"supervised":[62,102],"approach":[63,144,162],"video,":[71],"which":[72,117],"can":[73],"learn":[74],"robust":[76],"prediction":[78],"model":[79],"very":[82],"limited":[83],"and":[87,132,155],"large":[89],"amount":[90],"that":[95,159],"could":[96],"be":[97],"easily":[98],"generated":[99],"approach.":[103],"Furthermore,":[104],"we":[105],"propose":[106],"spatiotemporal":[108],"cascade":[109],"neural":[110],"network":[111],"architecture":[112],"two":[118],"convolutional":[120],"networks":[121],"are":[122],"cascaded":[123],"evaluate":[125],"visual":[127],"from":[129],"both":[130],"spatial":[131],"temporal":[133],"cues":[134],"lead":[136],"optimal":[138],"prediction.":[141],"The":[142],"proposed":[143,161],"extensively":[146],"evaluated":[147],"on":[148],"widely":[150],"used":[151],"challenging":[152],"sets,":[154],"experiments":[157],"demonstrate":[158],"our":[160],"outperforms":[164],"state-of-the-art":[166],"models.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}