{"id":"https://openalex.org/W1938976761","doi":"https://doi.org/10.1109/cvpr.2015.7298959","title":"Feedforward semantic segmentation with zoom-out features","display_name":"Feedforward semantic segmentation with zoom-out features","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1938976761","doi":"https://doi.org/10.1109/cvpr.2015.7298959","mag":"1938976761"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7298959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5059944840","display_name":"Mohammadreza Mostajabi","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammadreza Mostajabi","raw_affiliation_strings":["Toyota Technological Institute at Chicago","[Toyota Technological Institute at Chicago, USA]"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute at Chicago","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"[Toyota Technological Institute at Chicago, USA]","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015322848","display_name":"Payman Yadollahpour","orcid":"https://orcid.org/0000-0003-1984-5014"},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Payman Yadollahpour","raw_affiliation_strings":["Toyota Technological Institute at Chicago","[Toyota Technological Institute at Chicago, USA]"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute at Chicago","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"[Toyota Technological Institute at Chicago, USA]","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019380351","display_name":"Gregory Shakhnarovich","orcid":"https://orcid.org/0000-0003-4700-9398"},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory Shakhnarovich","raw_affiliation_strings":["Toyota Technological Institute at Chicago","[Toyota Technological Institute at Chicago, USA]"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute at Chicago","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"[Toyota Technological Institute at Chicago, USA]","institution_ids":["https://openalex.org/I160992636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059944840"],"corresponding_institution_ids":["https://openalex.org/I160992636"],"apc_list":null,"apc_paid":null,"fwci":46.0549,"has_fulltext":false,"cited_by_count":464,"citation_normalized_percentile":{"value":0.99843593,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3376","last_page":"3385"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9997000098228455,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7742639780044556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7389014959335327},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.736221194267273},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6140792369842529},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6103538870811462},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.5778855085372925},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.5722846388816833},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5514222979545593},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4786442518234253},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4586714208126068},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4285731911659241}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742639780044556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7389014959335327},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.736221194267273},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6140792369842529},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6103538870811462},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.5778855085372925},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.5722846388816833},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5514222979545593},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4786442518234253},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4586714208126068},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4285731911659241},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2015.7298959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6200000047683716}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W78159342","https://openalex.org/W1423339008","https://openalex.org/W1507506748","https://openalex.org/W1546771929","https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1938976761","https://openalex.org/W1948751323","https://openalex.org/W1992234703","https://openalex.org/W2013777358","https://openalex.org/W2022508996","https://openalex.org/W2035136470","https://openalex.org/W2037227137","https://openalex.org/W2046382188","https://openalex.org/W2054279472","https://openalex.org/W2088049833","https://openalex.org/W2090997445","https://openalex.org/W2095705004","https://openalex.org/W2102605133","https://openalex.org/W2106317217","https://openalex.org/W2106471914","https://openalex.org/W2115150266","https://openalex.org/W2117539524","https://openalex.org/W2118246710","https://openalex.org/W2124592697","https://openalex.org/W2130942329","https://openalex.org/W2144794286","https://openalex.org/W2150609397","https://openalex.org/W2153378748","https://openalex.org/W2155494658","https://openalex.org/W2155893237","https://openalex.org/W2158842374","https://openalex.org/W2163605009","https://openalex.org/W2182705849","https://openalex.org/W2186629860","https://openalex.org/W2271601362","https://openalex.org/W2395611524","https://openalex.org/W2535516436","https://openalex.org/W2545985378","https://openalex.org/W2962835968","https://openalex.org/W2963048250","https://openalex.org/W3186546642","https://openalex.org/W6628124331","https://openalex.org/W6632360823","https://openalex.org/W6637373629","https://openalex.org/W6640054144","https://openalex.org/W6640295612","https://openalex.org/W6640759395","https://openalex.org/W6659984577","https://openalex.org/W6673395892","https://openalex.org/W6674330103","https://openalex.org/W6675895156","https://openalex.org/W6677651945","https://openalex.org/W6678459986","https://openalex.org/W6682137105","https://openalex.org/W6682354963","https://openalex.org/W6683346193","https://openalex.org/W6684191040","https://openalex.org/W6686210315","https://openalex.org/W6686993759","https://openalex.org/W6694096821"],"related_works":["https://openalex.org/W2788595494","https://openalex.org/W2286391053","https://openalex.org/W2982600058","https://openalex.org/W2244676099","https://openalex.org/W3172556642","https://openalex.org/W3157456843","https://openalex.org/W1990150827","https://openalex.org/W2036676347","https://openalex.org/W1963486701","https://openalex.org/W2312483540"],"abstract_inverted_index":{"We":[0,9],"introduce":[1],"a":[2,21,77],"purely":[3],"feed-forward":[4],"architecture":[5,82],"for":[6],"semantic":[7],"segmentation.":[8],"map":[10],"small":[11],"image":[12,52],"elements":[13],"(superpixels)":[14],"to":[15,42],"rich":[16],"feature":[17],"representations":[18],"extracted":[19],"from":[20,36],"sequence":[22],"of":[23,26],"nested":[24],"regions":[25,30],"increasing":[27],"extent.":[28],"These":[29],"are":[31,74],"obtained":[32],"by":[33,76],"\u201czooming":[34],"out\u201d":[35],"the":[37,40,51,55,88],"superpixel":[38],"all":[39],"way":[41],"scene-level":[43],"resolution.":[44],"This":[45],"approach":[46],"exploits":[47],"statistical":[48],"structure":[49],"in":[50,54],"and":[53,65,69],"label":[56],"space":[57],"without":[58],"setting":[59],"up":[60],"explicit":[61],"structured":[62],"prediction":[63],"mechanisms,":[64],"thus":[66],"avoids":[67],"complex":[68],"expensive":[70],"inference.":[71],"Instead":[72],"superpixels":[73],"classified":[75],"feedforward":[78],"multilayer":[79],"network.":[80],"Our":[81],"achieves":[83],"69.6%":[84],"average":[85],"accuracy":[86],"on":[87],"PASCAL":[89],"VOC":[90],"2012":[91],"test":[92],"set.":[93]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":43},{"year":2020,"cited_by_count":55},{"year":2019,"cited_by_count":65},{"year":2018,"cited_by_count":65},{"year":2017,"cited_by_count":88},{"year":2016,"cited_by_count":72},{"year":2015,"cited_by_count":21},{"year":2014,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}