{"id":"https://openalex.org/W4399144479","doi":"https://doi.org/10.1145/3654823.3654851","title":"C2F-YOLO: A Coarse-to-Fine Object Detection Framework Based on YOLO","display_name":"C2F-YOLO: A Coarse-to-Fine Object Detection Framework Based on YOLO","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4399144479","doi":"https://doi.org/10.1145/3654823.3654851"},"language":"en","primary_location":{"id":"doi:10.1145/3654823.3654851","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654851","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","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/A5101871259","display_name":"Jingmin Pan","orcid":"https://orcid.org/0009-0008-0514-1941"},"institutions":[{"id":"https://openalex.org/I4210145049","display_name":"Anhui Institute of Information Technology","ror":"https://ror.org/04mw2ty13","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145049"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingmin Pan","raw_affiliation_strings":["Anhui Institute of Information Technology, China"],"raw_orcid":"https://orcid.org/0009-0008-0514-1941","affiliations":[{"raw_affiliation_string":"Anhui Institute of Information Technology, China","institution_ids":["https://openalex.org/I4210145049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111215280","display_name":"Sukui Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145049","display_name":"Anhui Institute of Information Technology","ror":"https://ror.org/04mw2ty13","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145049"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sukui Xu","raw_affiliation_strings":["Anhui Institute of Information Technology, China"],"raw_orcid":"https://orcid.org/0009-0008-0490-5444","affiliations":[{"raw_affiliation_string":"Anhui Institute of Information Technology, China","institution_ids":["https://openalex.org/I4210145049"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhiyuan Cheng","orcid":"https://orcid.org/0000-0003-0688-9667"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiyuan Cheng","raw_affiliation_strings":["iFLYTEK Co., Ltd., China"],"raw_orcid":"https://orcid.org/0000-0003-0688-9667","affiliations":[{"raw_affiliation_string":"iFLYTEK Co., Ltd., China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103127780","display_name":"S. Lian","orcid":"https://orcid.org/0009-0009-3105-7353"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shun Lian","raw_affiliation_strings":["iFLYTEK Co., Ltd., China"],"raw_orcid":"https://orcid.org/0009-0009-3105-7353","affiliations":[{"raw_affiliation_string":"iFLYTEK Co., Ltd., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101871259"],"corresponding_institution_ids":["https://openalex.org/I4210145049"],"apc_list":null,"apc_paid":null,"fwci":1.6665,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84766846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"150","last_page":"157"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983999729156494,"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":0.9983999729156494,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9750999808311462,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8065269589424133},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7104835510253906},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.6815471053123474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5956190824508667},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5401239991188049},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.49175575375556946},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44793593883514404},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.43026846647262573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3797754645347595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.27286767959594727},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.1052219569683075}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8065269589424133},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7104835510253906},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.6815471053123474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5956190824508667},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5401239991188049},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.49175575375556946},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44793593883514404},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.43026846647262573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3797754645347595},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27286767959594727},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.1052219569683075},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3654823.3654851","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654851","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2102605133","https://openalex.org/W2336589871","https://openalex.org/W2560920409","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W3003999301","https://openalex.org/W4236965008","https://openalex.org/W4306967787","https://openalex.org/W4313525589","https://openalex.org/W4362598372","https://openalex.org/W4378676954","https://openalex.org/W4378676959","https://openalex.org/W4388823657"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W2949096641"],"abstract_inverted_index":{"Benefiting":[0],"from":[1,173,198],"the":[2,60,66,101,149,156,174,178,188,199,213,227],"development":[3],"of":[4,62,68,103,116,170,195,215],"deep":[5],"learning":[6],"in":[7,15,29,65,95,108,142],"recent":[8],"years,":[9],"there":[10],"have":[11],"been":[12],"significant":[13],"advancements":[14],"object":[16,49,63,105,128],"detection.":[17],"In":[18],"smart":[19,38,69,109],"classroom":[20],"environments,":[21],"student":[22,54,97,140],"behaviors":[23,141],"vary":[24],"widely":[25],"due":[26],"to":[27,36,44,52,92,167,177,181,192,211],"differences":[28],"layout,":[30],"lighting,":[31],"and":[32,78,137,155],"other":[33],"factors":[34],"unique":[35],"each":[37],"classroom.":[39],"This":[40],"variability":[41],"often":[42],"leads":[43],"behavior":[45],"confusion":[46],"when":[47],"using":[48],"detection":[50,64,106,129],"algorithms":[51],"recognize":[53],"actions,":[55],"which":[56,135],"has":[57],"somewhat":[58],"hindered":[59],"progress":[61],"field":[67],"education.":[70],"Therefore,":[71],"addressing":[72],"this":[73,82,84],"issue":[74],"is":[75,165,190],"both":[76],"challenging":[77],"meaningful.":[79],"To":[80],"tackle":[81],"problem,":[83],"paper":[85],"proposes":[86],"a":[87,123,143],"novel":[88,124],"framework":[89,114,130],"called":[90],"C2F-YOLO":[91],"eliminate":[93],"ambiguities":[94],"discerning":[96],"behaviors,":[98],"thereby":[99],"enhancing":[100],"performance":[102],"coarse-to-fine":[104,127,144],"tasks":[107],"education":[110],"settings.":[111],"Specifically,":[112],"our":[113,207,216],"consists":[115],"three":[117],"main":[118],"parts.":[119],"Firstly,":[120],"we":[121,147,220],"introduce":[122],"method":[125],"about":[126],"based":[131],"on":[132,206],"YOLO,":[133],"C2F-YOLO,":[134],"identifies":[136],"refines":[138],"ambiguous":[139],"manner.":[145],"Secondly,":[146],"propose":[148],"cross-stage":[150],"connection":[151],"module":[152,160],"named":[153,161],"CSCM":[154,164],"multi-scale":[157],"feature":[158],"fusion":[159],"FSFM.":[162],"The":[163],"used":[166,191],"transfer":[168],"features":[169,194],"different":[171,196],"scales":[172,197],"first":[175,200],"stage":[176,180],"second":[179],"learn":[182],"more":[183],"diverse":[184],"dimensional":[185],"features,":[186],"while":[187],"FSFM":[189],"merge":[193],"stages.":[201],"We":[202],"conducted":[203],"extensive":[204],"experiments":[205],"proprietary":[208],"real-world":[209],"dataset":[210],"demonstrate":[212],"superiority":[214],"proposed":[217],"framework.":[218],"Remarkably,":[219],"achieved":[221],"impressive":[222],"results":[223],"without":[224],"significantly":[225],"increasing":[226],"parameter":[228],"count.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}