{"id":"https://openalex.org/W2970687308","doi":"https://doi.org/10.1109/icip.2019.8803285","title":"Learning Cascaded Siamese Networks for High Performance Visual Tracking","display_name":"Learning Cascaded Siamese Networks for High Performance Visual Tracking","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970687308","doi":"https://doi.org/10.1109/icip.2019.8803285","mag":"2970687308"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5028272399","display_name":"Peng Gao","orcid":"https://orcid.org/0000-0003-2230-3937"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Gao","raw_affiliation_strings":["Department of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051969162","display_name":"Yipeng Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Yipeng Ma","raw_affiliation_strings":["Department of Electronic and Information Engineering, Huawei Noah\u2019s Ark Lab., Shenzhen","Department of Electronic and Information Engineering, Huawei Noah's Ark Lab., Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Information Engineering, Huawei Noah\u2019s Ark Lab., Shenzhen","institution_ids":["https://openalex.org/I4210159102"]},{"raw_affiliation_string":"Department of Electronic and Information Engineering, Huawei Noah's Ark Lab., Shenzhen","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025121954","display_name":"Ru-Yue Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100005","display_name":"Silicon Technologies (United States)","ror":"https://ror.org/013qwzt07","country_code":"US","type":"company","lineage":["https://openalex.org/I4210100005"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruyue Yuan","raw_affiliation_strings":["Department of Electronic and Information Engineering, HiSilicon Technologies Co., Ltd, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Information Engineering, HiSilicon Technologies Co., Ltd, Shenzhen","institution_ids":["https://openalex.org/I4210100005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108236996","display_name":"Liyi Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liyi Xiao","raw_affiliation_strings":["Department of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100455958","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0003-3462-8472"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Department of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4575,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.70740279,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"37","issue":null,"first_page":"3078","last_page":"3082"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11019","display_name":"Image Enhancement Techniques","score":0.9783999919891357,"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":0.9711999893188477,"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/subnetwork","display_name":"Subnetwork","score":0.9834355115890503},{"id":"https://openalex.org/keywords/subnet","display_name":"Subnet","score":0.8117468357086182},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7616028785705566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6881120204925537},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5253105759620667},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.4785524010658264},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4687027633190155},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.46164149045944214},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4434782564640045},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4251474142074585},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.41746559739112854},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4102261960506439},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3493928909301758},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3195938467979431},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1412942111492157},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08327382802963257}],"concepts":[{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.9834355115890503},{"id":"https://openalex.org/C21099817","wikidata":"https://www.wikidata.org/wiki/Q7631721","display_name":"Subnet","level":2,"score":0.8117468357086182},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7616028785705566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6881120204925537},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5253105759620667},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.4785524010658264},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4687027633190155},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.46164149045944214},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4434782564640045},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4251474142074585},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.41746559739112854},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4102261960506439},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3493928909301758},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3195938467979431},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1412942111492157},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08327382802963257},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1857884451","https://openalex.org/W1995903777","https://openalex.org/W1997121481","https://openalex.org/W2089961441","https://openalex.org/W2117539524","https://openalex.org/W2126302311","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2470394683","https://openalex.org/W2518013266","https://openalex.org/W2557641257","https://openalex.org/W2608627404","https://openalex.org/W2887556118","https://openalex.org/W2899321954","https://openalex.org/W2916780012","https://openalex.org/W2941201280","https://openalex.org/W2952558221","https://openalex.org/W2962799386","https://openalex.org/W2962968160","https://openalex.org/W2963589976","https://openalex.org/W2964111344"],"related_works":["https://openalex.org/W2356206668","https://openalex.org/W2060724872","https://openalex.org/W2131631951","https://openalex.org/W4386946857","https://openalex.org/W4296780664","https://openalex.org/W2168810502","https://openalex.org/W1911510050","https://openalex.org/W4205469791","https://openalex.org/W3199360896","https://openalex.org/W2980378073"],"abstract_inverted_index":{"Visual":[0],"tracking":[1,18,96,129],"is":[2,28,49,83,106,145],"one":[3],"of":[4],"the":[5,57,61,65,88,94,100,113,128,149],"most":[6],"challenging":[7],"computer":[8],"vision":[9],"problems.":[10],"In":[11],"order":[12],"to":[13,56,70,85,121],"achieve":[14],"high":[15],"performance":[16,130,162],"visual":[17],"in":[19,163],"various":[20],"negative":[21],"scenarios,":[22],"a":[23,39,43,50],"novel":[24],"cascaded":[25],"Siamese":[26,53],"network":[27],"proposed":[29,158],"and":[30,42,64,75,92,109,142],"developed":[31],"based":[32,98,138],"on":[33,99,139],"two":[34],"different":[35],"deep":[36],"learning":[37],"networks:":[38],"matching":[40,47,104],"subnetwork":[41,48,105,115,135],"classification":[44,81,101,114,134,143,150],"subnetwork.":[45,151],"The":[46,80,103],"fully":[51],"convolutional":[52],"network.":[54],"According":[55],"similarity":[58,141],"score":[59],"between":[60],"exemplar":[62],"image":[63],"candidate":[66,78,90],"image,":[67],"it":[68],"aims":[69],"search":[71],"possible":[72],"object":[73],"positions":[74],"crop":[76],"scaled":[77],"patches.":[79],"subnet-work":[82],"designed":[84],"further":[86],"evaluate":[87],"cropped":[89],"patches":[91],"determine":[93],"optimal":[95],"results":[97,154],"score.":[102],"trained":[107],"offline":[108],"fixed":[110],"online,":[111],"while":[112],"performs":[116],"stochastic":[117],"gradient":[118],"descent":[119],"online":[120],"learn":[122],"more":[123],"target-specific":[124],"information.":[125],"To":[126],"improve":[127],"further,":[131],"an":[132],"effective":[133],"update":[136],"method":[137],"both":[140],"scores":[144],"utilized":[146],"for":[147],"updating":[148],"Extensive":[152],"experimental":[153],"demonstrate":[155],"that":[156],"our":[157],"approach":[159],"achieves":[160],"state-of-the-art":[161],"recent":[164],"benchmarks.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
