{"id":"https://openalex.org/W1965846078","doi":"https://doi.org/10.1109/cvpr.2012.6247785","title":"Learning attention map from images","display_name":"Learning attention map from images","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W1965846078","doi":"https://doi.org/10.1109/cvpr.2012.6247785","mag":"1965846078"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247785","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5102831128","display_name":"Yao Lu","orcid":"https://orcid.org/0000-0002-3147-2081"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yao Lu","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691613","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-3942-0593"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625873","display_name":"Cheng Jin","orcid":"https://orcid.org/0000-0003-3063-1957"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Jin","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003418019","display_name":"Xiangyang Xue","orcid":"https://orcid.org/0000-0002-4897-9209"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Xue","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102831128"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":2.4709,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89859949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1067","last_page":"1074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.9714999794960022,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8027206659317017},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7392463088035583},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6750790476799011},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6558157801628113},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5701852440834045},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.513769268989563},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4974105656147003},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4747636318206787},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4730105698108673},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47025835514068604},{"id":"https://openalex.org/keywords/figure\u2013ground","display_name":"Figure\u2013ground","score":0.4466427266597748},{"id":"https://openalex.org/keywords/top-down-and-bottom-up-design","display_name":"Top-down and bottom-up design","score":0.42231035232543945},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41598182916641235},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40245380997657776},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06569641828536987}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8027206659317017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7392463088035583},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6750790476799011},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6558157801628113},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5701852440834045},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.513769268989563},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4974105656147003},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4747636318206787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4730105698108673},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47025835514068604},{"id":"https://openalex.org/C104319648","wikidata":"https://www.wikidata.org/wiki/Q1412040","display_name":"Figure\u2013ground","level":3,"score":0.4466427266597748},{"id":"https://openalex.org/C135798126","wikidata":"https://www.wikidata.org/wiki/Q2167279","display_name":"Top-down and bottom-up design","level":2,"score":0.42231035232543945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41598182916641235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40245380997657776},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06569641828536987},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2012.6247785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247785","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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":40,"referenced_works":["https://openalex.org/W1510835000","https://openalex.org/W1531486232","https://openalex.org/W1566135517","https://openalex.org/W1655654231","https://openalex.org/W1877469910","https://openalex.org/W1890779811","https://openalex.org/W1998062602","https://openalex.org/W1999478155","https://openalex.org/W2006902234","https://openalex.org/W2029661329","https://openalex.org/W2039461297","https://openalex.org/W2054279472","https://openalex.org/W2073767010","https://openalex.org/W2095315834","https://openalex.org/W2095844239","https://openalex.org/W2100470808","https://openalex.org/W2103666701","https://openalex.org/W2109812093","https://openalex.org/W2110764733","https://openalex.org/W2112301665","https://openalex.org/W2120419212","https://openalex.org/W2121600399","https://openalex.org/W2121947860","https://openalex.org/W2125310925","https://openalex.org/W2125637308","https://openalex.org/W2128272608","https://openalex.org/W2130047666","https://openalex.org/W2157652882","https://openalex.org/W2161502316","https://openalex.org/W2168555635","https://openalex.org/W2169561119","https://openalex.org/W2171590216","https://openalex.org/W3097096317","https://openalex.org/W4285719527","https://openalex.org/W6631799520","https://openalex.org/W6639286751","https://openalex.org/W6660196224","https://openalex.org/W6674793120","https://openalex.org/W6683908240","https://openalex.org/W6684745935"],"related_works":["https://openalex.org/W2044641672","https://openalex.org/W2048788251","https://openalex.org/W2174043808","https://openalex.org/W2047929095","https://openalex.org/W2898826419","https://openalex.org/W2153888769","https://openalex.org/W4253526137","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290"],"abstract_inverted_index":{"While":[0],"bottom-up":[1],"and":[2,11,44,82,96],"top-down":[3],"processes":[4],"have":[5],"shown":[6],"effectiveness":[7],"during":[8],"predicting":[9,50,93],"attention":[10,27,71,94],"eye":[12],"fixation":[13],"maps":[14,34],"on":[15,62],"images,":[16],"in":[17,92],"this":[18],"paper,":[19],"inspired":[20],"by":[21],"the":[22,36],"perceptual":[23],"organization":[24],"mechanism":[25],"before":[26],"selection,":[28,95],"we":[29,56],"propose":[30],"to":[31,40,65,77],"utilize":[32],"figure-ground":[33,88],"for":[35,53],"purpose.":[37],"So":[38],"as":[39],"take":[41],"both":[42,79],"pixel-wise":[43],"region-wise":[45],"interactions":[46],"into":[47],"consideration":[48],"when":[49],"label":[51],"probabilities":[52],"each":[54],"pixel,":[55],"develop":[57],"a":[58],"context-aware":[59],"model":[60,99],"based":[61],"multiple":[63],"segmentation":[64],"obtain":[66],"final":[67],"results.":[68],"The":[69],"MIT":[70],"dataset":[72],"[14]":[73],"is":[74],"applied":[75],"finally":[76],"evaluate":[78],"new":[80],"features":[81],"model.":[83],"Quantitative":[84],"experiments":[85],"demonstrate":[86],"that":[87],"cues":[89],"are":[90],"valid":[91],"our":[97],"proposed":[98],"produces":[100],"improvements":[101],"over":[102],"baseline":[103],"method.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}