{"id":"https://openalex.org/W2524324335","doi":"https://doi.org/10.1145/2964284.2967252","title":"CNN vs. SIFT for Image Retrieval","display_name":"CNN vs. SIFT for Image Retrieval","publication_year":2016,"publication_date":"2016-09-29","ids":{"openalex":"https://openalex.org/W2524324335","doi":"https://doi.org/10.1145/2964284.2967252","mag":"2524324335"},"language":"en","primary_location":{"id":"doi:10.1145/2964284.2967252","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2964284.2967252","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM international conference on Multimedia","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/A5101967245","display_name":"Ke Yan","orcid":"https://orcid.org/0000-0002-0034-9013"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ke Yan","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631216","display_name":"Yaowei Wang","orcid":"https://orcid.org/0000-0003-2197-9038"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowei Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021841223","display_name":"Dawei Liang","orcid":"https://orcid.org/0000-0002-5520-3011"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Liang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058066577","display_name":"Tiejun Huang","orcid":"https://orcid.org/0000-0002-4234-6099"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejun Huang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023918894","display_name":"Yonghong Tian","orcid":"https://orcid.org/0000-0002-2978-5935"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghong Tian","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101967245"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":6.0122,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":{"value":0.97704197,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"407","last_page":"411"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9965000152587891,"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":0.9939000010490417,"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/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.9392451047897339},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8121719360351562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8042547702789307},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.738814651966095},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6923911571502686},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6083918809890747},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5617501735687256},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5182509422302246},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5164749622344971},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.5075298547744751},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4649798572063446},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.46273431181907654},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4519887864589691},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41470950841903687},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41111087799072266}],"concepts":[{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.9392451047897339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8121719360351562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8042547702789307},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.738814651966095},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6923911571502686},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6083918809890747},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5617501735687256},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5182509422302246},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5164749622344971},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.5075298547744751},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4649798572063446},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.46273431181907654},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4519887864589691},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41470950841903687},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41111087799072266},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2964284.2967252","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2964284.2967252","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM international conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4272565921","display_name":null,"funder_award_id":"61390515, 61425025 and 61471042","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W204268067","https://openalex.org/W1515236863","https://openalex.org/W1524680991","https://openalex.org/W1556531089","https://openalex.org/W1783842908","https://openalex.org/W1909011730","https://openalex.org/W1979931042","https://openalex.org/W1984309565","https://openalex.org/W2038752770","https://openalex.org/W2045143396","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2123229215","https://openalex.org/W2128017662","https://openalex.org/W2141362318","https://openalex.org/W2145072179","https://openalex.org/W2147238549","https://openalex.org/W2147854204","https://openalex.org/W2148809531","https://openalex.org/W2151103935","https://openalex.org/W2163605009","https://openalex.org/W2164022341","https://openalex.org/W2174726731","https://openalex.org/W2204975001","https://openalex.org/W2212216676","https://openalex.org/W2296096135","https://openalex.org/W2404781972","https://openalex.org/W2613718673","https://openalex.org/W2618530766","https://openalex.org/W2953106684"],"related_works":["https://openalex.org/W2063218608","https://openalex.org/W4386105885","https://openalex.org/W2184288218","https://openalex.org/W2947282851","https://openalex.org/W2374066281","https://openalex.org/W4387423606","https://openalex.org/W2071180033","https://openalex.org/W2036058638","https://openalex.org/W2528082075","https://openalex.org/W155590726"],"abstract_inverted_index":{"In":[0,57,97],"the":[1,28,47,64,123],"past":[2],"decade,":[3],"SIFT":[4,84,90],"is":[5],"widely":[6],"used":[7,102],"in":[8,17,31,91,111],"most":[9],"vision":[10],"tasks":[11,33],"such":[12,34],"as":[13,35],"image":[14,36,48,78,119],"retrieval.":[15],"While":[16],"recent":[18],"several":[19,32],"years,":[20],"deep":[21],"convolutional":[22],"neural":[23],"networks":[24],"(CNN)":[25],"features":[26,53,68],"achieve":[27],"state-of-the-art":[29,131],"performance":[30],"classification":[37],"and":[38,83,89,94,108,122],"object":[39],"detection.":[40],"Thus":[41],"a":[42,92],"natural":[43],"question":[44],"arises:":[45],"for":[46,55],"retrieval":[49,120,132],"task,":[50],"can":[51,100],"CNN":[52,82,88],"substitute":[54],"SIFT?":[56],"this":[58,73],"paper,":[59],"we":[60,75],"experimentally":[61],"demonstrate":[62],"that":[63,127],"two":[65],"kinds":[66],"of":[67],"are":[69,115],"highly":[70],"complementary.":[71],"Following":[72],"fact,":[74],"propose":[76],"an":[77],"representation":[79],"model,":[80],"complementary":[81,95],"(CCS),":[85],"to":[86,103],"fuse":[87],"multi-level":[93],"way.":[96],"particular,":[98],"it":[99],"be":[101],"simultaneously":[104],"describe":[105],"scene-level,":[106],"object-level":[107],"point-level":[109],"contents":[110],"images.":[112],"Extensive":[113],"experiments":[114],"conducted":[116],"on":[117],"four":[118],"benchmarks,":[121],"experimental":[124],"results":[125],"show":[126],"our":[128],"CCS":[129],"achieves":[130],"results.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":14}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
