{"id":"https://openalex.org/W2891108313","doi":"https://doi.org/10.1145/3240876.3240923","title":"Salient object detection via multi-scale neural network","display_name":"Salient object detection via multi-scale neural network","publication_year":2018,"publication_date":"2018-08-17","ids":{"openalex":"https://openalex.org/W2891108313","doi":"https://doi.org/10.1145/3240876.3240923","mag":"2891108313"},"language":"en","primary_location":{"id":"doi:10.1145/3240876.3240923","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240876.3240923","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/A5076329786","display_name":"Weiqian Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166603","display_name":"Jinling Institute of Technology","ror":"https://ror.org/05em1gq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166603"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiqian Lu","raw_affiliation_strings":["Nanjing University Jinling College"],"affiliations":[{"raw_affiliation_string":"Nanjing University Jinling College","institution_ids":["https://openalex.org/I4210166603","https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101546753","display_name":"Gangshan Wu","orcid":"https://orcid.org/0000-0003-1391-1762"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gangshan Wu","raw_affiliation_strings":["Nanjing University"],"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076329786"],"corresponding_institution_ids":["https://openalex.org/I4210166603","https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09568251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9775000214576721,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9771000146865845,"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":0.8026368618011475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6880925297737122},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6679620742797852},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6651591062545776},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6399410963058472},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5973599553108215},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5889784693717957},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5798435211181641},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5757879018783569},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5169245600700378},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4824450612068176},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4515085816383362},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4298584461212158},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41622740030288696},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40638452768325806},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10247117280960083},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.10064727067947388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8026368618011475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6880925297737122},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6679620742797852},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6651591062545776},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6399410963058472},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5973599553108215},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5889784693717957},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5798435211181641},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5757879018783569},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5169245600700378},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4824450612068176},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4515085816383362},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4298584461212158},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41622740030288696},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40638452768325806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10247117280960083},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.10064727067947388},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3240876.3240923","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240876.3240923","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W21025885","https://openalex.org/W1686810756","https://openalex.org/W1897243830","https://openalex.org/W1982075130","https://openalex.org/W2002781701","https://openalex.org/W2039313011","https://openalex.org/W2065985528","https://openalex.org/W2068288374","https://openalex.org/W2097117768","https://openalex.org/W2100470808","https://openalex.org/W2124351162","https://openalex.org/W2126532873","https://openalex.org/W2127807804","https://openalex.org/W2131297486","https://openalex.org/W2157381954","https://openalex.org/W2157554677","https://openalex.org/W2163605009","https://openalex.org/W2211996548","https://openalex.org/W2294849438","https://openalex.org/W2395611524","https://openalex.org/W2962850830","https://openalex.org/W2963840672"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1990856605","https://openalex.org/W2964954556","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"Salient":[0],"object":[1,33],"detection,":[2],"a":[3,18,69],"fundamental":[4],"of":[5,47],"many":[6],"computer":[7],"vision":[8],"tasks,":[9],"aims":[10],"to":[11,41,74,95,112],"find":[12],"the":[13,44,48,52,63,76,81,86,93,114],"most":[14],"attractive":[15],"objects":[16],"in":[17],"given":[19],"image.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24,36,61,84],"propose":[25,37],"an":[26],"end-to-end":[27],"multi-scale":[28],"neural":[29],"network":[30,94],"for":[31],"salient":[32],"detection.":[34],"Firstly,":[35],"heterogeneous":[38],"dilated":[39,58],"block":[40],"effectively":[42],"increases":[43],"receptive":[45],"field":[46],"network,":[49],"while":[50],"alleviating":[51],"gridding":[53],"effect":[54],"problem":[55],"caused":[56],"by":[57],"convolution.":[59],"Secondly,":[60],"replace":[62],"traditional":[64],"interpolation":[65],"up-sampling":[66,72],"layer":[67],"with":[68],"fully":[70],"learnable":[71],"module":[73],"solve":[75],"blurry":[77],"artifacts":[78],"and":[79,107,110],"improve":[80],"accuracy.":[82],"Finally,":[83],"calculate":[85],"loss":[87],"at":[88],"three":[89],"different":[90],"scales,":[91],"enabling":[92],"learn":[96],"better":[97],"through":[98],"back-propagation.":[99],"The":[100],"proposed":[101],"method":[102],"is":[103],"validated":[104],"on":[105],"MSRA":[106],"ECSSD":[108],"datasets,":[109],"shown":[111],"outperform":[113],"state-of-the-art":[115],"methods.":[116]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
