{"id":"https://openalex.org/W1930528368","doi":"https://doi.org/10.1109/cvpr.2015.7299067","title":"DeepEdge: A multi-scale bifurcated deep network for top-down contour detection","display_name":"DeepEdge: A multi-scale bifurcated deep network for top-down contour detection","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1930528368","doi":"https://doi.org/10.1109/cvpr.2015.7299067","mag":"1930528368"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7299067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299067","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/A5081800468","display_name":"Gedas Bertasius","orcid":"https://orcid.org/0000-0003-1800-4790"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]},{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gedas Bertasius","raw_affiliation_strings":["University of Pennsylvania","University of Pennsylvania, Philadelphia 19104, United States"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]},{"raw_affiliation_string":"University of Pennsylvania, Philadelphia 19104, United States","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081456949","display_name":"Jianbo Shi","orcid":"https://orcid.org/0000-0003-2637-1929"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]},{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianbo Shi","raw_affiliation_strings":["University of Pennsylvania","University of Pennsylvania, Philadelphia 19104, United States"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]},{"raw_affiliation_string":"University of Pennsylvania, Philadelphia 19104, United States","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082736347","display_name":"Lorenzo Torresani","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166639","display_name":"Dartmouth Hospital","ror":"https://ror.org/02j3qj605","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210166639"]},{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Lorenzo Torresani","raw_affiliation_strings":["Dartmouth College","Dartmouth College, Hanover, NH, 03755, United States"],"affiliations":[{"raw_affiliation_string":"Dartmouth College","institution_ids":["https://openalex.org/I4210166639","https://openalex.org/I107672454"]},{"raw_affiliation_string":"Dartmouth College, Hanover, NH, 03755, United States","institution_ids":["https://openalex.org/I107672454"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081800468"],"corresponding_institution_ids":["https://openalex.org/I36788626","https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":31.456,"has_fulltext":false,"cited_by_count":528,"citation_normalized_percentile":{"value":0.99721774,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4380","last_page":"4389"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9993000030517578,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.820433497428894},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7789241671562195},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7641503810882568},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7188195586204529},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7036528587341309},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5942302942276001},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5870056748390198},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5589832663536072},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5329773426055908},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5048611760139465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4928174316883087},{"id":"https://openalex.org/keywords/object-class-detection","display_name":"Object-class detection","score":0.4652251899242401},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4547613561153412},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.12365555763244629},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0746370255947113}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.820433497428894},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7789241671562195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7641503810882568},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7188195586204529},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7036528587341309},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5942302942276001},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5870056748390198},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5589832663536072},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5329773426055908},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5048611760139465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4928174316883087},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.4652251899242401},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4547613561153412},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.12365555763244629},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0746370255947113},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2015.7299067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299067","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W97134437","https://openalex.org/W105270443","https://openalex.org/W1563795667","https://openalex.org/W1842610785","https://openalex.org/W1903029394","https://openalex.org/W1948751323","https://openalex.org/W1976047850","https://openalex.org/W1989684337","https://openalex.org/W1991367009","https://openalex.org/W1999478155","https://openalex.org/W2067191022","https://openalex.org/W2102605133","https://openalex.org/W2108927102","https://openalex.org/W2110158442","https://openalex.org/W2113325037","https://openalex.org/W2117539524","https://openalex.org/W2121927366","https://openalex.org/W2121947440","https://openalex.org/W2123602281","https://openalex.org/W2133267925","https://openalex.org/W2139212933","https://openalex.org/W2141376824","https://openalex.org/W2145023731","https://openalex.org/W2145287260","https://openalex.org/W2147414309","https://openalex.org/W2151049637","https://openalex.org/W2155893237","https://openalex.org/W2159372453","https://openalex.org/W2163605009","https://openalex.org/W2165140157","https://openalex.org/W2172014587","https://openalex.org/W2951277909","https://openalex.org/W2952020226","https://openalex.org/W2962883796","https://openalex.org/W2963542991","https://openalex.org/W3147600416","https://openalex.org/W4300336863","https://openalex.org/W6604023374","https://openalex.org/W6604191837","https://openalex.org/W6629368666","https://openalex.org/W6633802082","https://openalex.org/W6638650905","https://openalex.org/W6640054144","https://openalex.org/W6640759395","https://openalex.org/W6676267127","https://openalex.org/W6676698716","https://openalex.org/W6677651945","https://openalex.org/W6677945368","https://openalex.org/W6681853784","https://openalex.org/W6684191040","https://openalex.org/W6685427411","https://openalex.org/W6764062975","https://openalex.org/W6765897598","https://openalex.org/W7037270093"],"related_works":["https://openalex.org/W2901758161","https://openalex.org/W4205668735","https://openalex.org/W3204852000","https://openalex.org/W3126664501","https://openalex.org/W3209429418","https://openalex.org/W4297540035","https://openalex.org/W4312834249","https://openalex.org/W2997780656","https://openalex.org/W3013015374","https://openalex.org/W4366374902"],"abstract_inverted_index":{"Contour":[0],"detection":[1,13],"has":[2],"been":[3],"a":[4,36,79],"fundamental":[5],"component":[6],"in":[7],"many":[8],"image":[9],"segmentation":[10],"and":[11,29,49],"object":[12,41],"systems.":[14],"Most":[15],"previous":[16],"work":[17],"utilizes":[18],"low-level":[19,76],"features":[20,86],"such":[21,39],"as":[22,33,40,87],"texture":[23],"or":[24],"saliency":[25],"to":[26,58],"detect":[27],"contours":[28,51,74],"then":[30],"use":[31],"them":[32],"cues":[34,77,89],"for":[35,78,90],"higher-level":[37,80],"task":[38],"detection.":[42,92],"However,":[43],"we":[44,61,64,83],"claim":[45],"that":[46,63],"recognizing":[47],"objects":[48],"predicting":[50],"are":[52],"two":[53],"mutually":[54],"related":[55],"tasks.":[56],"Contrary":[57],"traditional":[59],"approaches,":[60],"show":[62],"can":[65],"invert":[66],"the":[67],"commonly":[68],"established":[69],"pipeline:":[70],"instead":[71],"of":[72],"detecting":[73],"with":[75],"recognition":[81],"task,":[82],"exploit":[84],"object-related":[85],"high-level":[88],"contour":[91]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":38},{"year":2024,"cited_by_count":44},{"year":2023,"cited_by_count":45},{"year":2022,"cited_by_count":50},{"year":2021,"cited_by_count":72},{"year":2020,"cited_by_count":55},{"year":2019,"cited_by_count":50},{"year":2018,"cited_by_count":62},{"year":2017,"cited_by_count":59},{"year":2016,"cited_by_count":37},{"year":2015,"cited_by_count":10}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
