{"id":"https://openalex.org/W2950557191","doi":"https://doi.org/10.1145/3323873.3325033","title":"Take Goods from Shelves","display_name":"Take Goods from Shelves","publication_year":2019,"publication_date":"2019-06-05","ids":{"openalex":"https://openalex.org/W2950557191","doi":"https://doi.org/10.1145/3323873.3325033","mag":"2950557191"},"language":"en","primary_location":{"id":"doi:10.1145/3323873.3325033","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3323873.3325033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 on International Conference on Multimedia Retrieval","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/A5100647393","display_name":"Hao Yu","orcid":"https://orcid.org/0000-0002-2111-6905"},"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":"Yu Hao","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084959430","display_name":"Yanwei Fu","orcid":"https://orcid.org/0000-0002-6595-6893"},"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":"Yanwei Fu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047962986","display_name":"Yu\u2013Gang Jiang","orcid":"https://orcid.org/0000-0002-1907-8567"},"institutions":[{"id":"https://openalex.org/I4210099297","display_name":"Jilian Technology Group (China)","ror":"https://ror.org/016q5ce10","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210099297"]},{"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":"Yu-Gang Jiang","raw_affiliation_strings":["Fudan University &amp; Jilian Technology Group (Video++), Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University &amp; Jilian Technology Group (Video++), Shanghai, China","institution_ids":["https://openalex.org/I4210099297","https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100647393"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":1.3159,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.84325533,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"271","last_page":"278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9958999752998352,"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":0.7569819688796997},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6467596292495728},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6139498949050903},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5901327729225159},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5875766277313232},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5458389520645142},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.5169774293899536},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4879721999168396},{"id":"https://openalex.org/keywords/goods-and-services","display_name":"Goods and services","score":0.4268287420272827},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4100792407989502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4032108783721924},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.18550023436546326},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.09996840357780457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7569819688796997},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6467596292495728},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6139498949050903},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5901327729225159},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5875766277313232},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5458389520645142},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.5169774293899536},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4879721999168396},{"id":"https://openalex.org/C187452473","wikidata":"https://www.wikidata.org/wiki/Q2897903","display_name":"Goods and services","level":2,"score":0.4268287420272827},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4100792407989502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4032108783721924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.18550023436546326},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.09996840357780457},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3323873.3325033","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3323873.3325033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G5098360972","display_name":null,"funder_award_id":"61622204, 61572134","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320720","display_name":"Indian Council of Medical Research","ror":"https://ror.org/0492wrx28"},{"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":33,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W1536680647","https://openalex.org/W1598866093","https://openalex.org/W1686810756","https://openalex.org/W1821462560","https://openalex.org/W1861492603","https://openalex.org/W1976349993","https://openalex.org/W1985060986","https://openalex.org/W1989970925","https://openalex.org/W2031489346","https://openalex.org/W2088049833","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2407521645","https://openalex.org/W2473930607","https://openalex.org/W2474280151","https://openalex.org/W2554863749","https://openalex.org/W2555440590","https://openalex.org/W2570343428","https://openalex.org/W2599765304","https://openalex.org/W2743388417","https://openalex.org/W2769291631","https://openalex.org/W2791220068","https://openalex.org/W2796347433","https://openalex.org/W2810376776","https://openalex.org/W2953106684","https://openalex.org/W2962966271","https://openalex.org/W2963037989","https://openalex.org/W2963446712","https://openalex.org/W2964189064","https://openalex.org/W2966730026","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W2737719445","https://openalex.org/W2898210368","https://openalex.org/W2382480268","https://openalex.org/W1976518449","https://openalex.org/W2732837990","https://openalex.org/W4206198161","https://openalex.org/W2363366881","https://openalex.org/W2052899165","https://openalex.org/W4292830139","https://openalex.org/W3035059915"],"abstract_inverted_index":{"Object":[0,106],"detection":[1,41,76],"for":[2,97],"automatic":[3],"visual":[4],"checkout":[5],"in":[6,14],"self-service":[7],"vending":[8],"machines":[9],"is":[10,109],"attracting":[11],"significant":[12],"attention":[13],"the":[15,40,44,53,99,122],"retail":[16,30],"industry.":[17],"However,":[18],"several":[19,116],"critical":[20],"challenges":[21],"have":[22],"not":[23],"received":[24],"enough":[25],"attention.":[26],"First,":[27],"large-scale,":[28],"high-quality":[29],"image":[31],"datasets":[32],"are":[33,119],"urgently":[34],"demanded":[35],"to":[36,50],"train":[37],"and":[38,90,112],"evaluate":[39],"models.":[42],"Second,":[43],"trained":[45],"models":[46,64],"should":[47],"be":[48],"able":[49],"cope":[51],"with":[52],"frequently":[54],"added":[55],"new":[56,72],"goods":[57],"at":[58],"low":[59],"cost,":[60],"while":[61],"most":[62],"cutting-edge":[63],"cannot.":[65],"In":[66,114],"this":[67],"paper,":[68],"we":[69],"propose":[70],"a":[71],"hierarchical":[73],"large-scale":[74],"object":[75],"dataset,":[77],"called":[78,102],"Take":[79],"Goods":[80],"from":[81],"Shelves":[82],"(TGFS),":[83],"containing":[84],"38K":[85],"images":[86],"of":[87],"24":[88],"fine-grained":[89],"3":[91],"coarse":[92],"classes.":[93],"A":[94],"preliminary":[95],"method":[96],"solving":[98],"goods-adding":[100],"problem,":[101],"Faster":[103],"R-CNN":[104],"Class-incremental":[105],"Detector":[107],"(FCIOD),":[108],"also":[110],"described":[111],"evaluated.":[113],"addition,":[115],"popular":[117],"methods":[118],"benchmarked":[120],"on":[121],"TGFS":[123],"dataset.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
