乐胖代购免代理版

{"id":"https://openalex.org/W4390873535","doi":"https://doi.org/10.1109/iccv51070.2023.00228","title":"Phasic Content Fusing Diffusion Model with Directional Distribution Consistency for Few-Shot Model Adaption","display_name":"Phasic Content Fusing Diffusion Model with Directional Distribution Consistency for Few-Shot Model Adaption","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390873535","doi":"https://doi.org/10.1109/iccv51070.2023.00228"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.00228","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.03729","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013427010","display_name":"Teng Hu","orcid":"https://orcid.org/0000-0003-4946-8977"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Teng Hu","raw_affiliation_strings":["Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021861529","display_name":"Jiangning Zhang","orcid":"https://orcid.org/0000-0001-8891-6766"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangning Zhang","raw_affiliation_strings":["Youtu Lab, Tencent"],"affiliations":[{"raw_affiliation_string":"Youtu Lab, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322342","display_name":"Liang Liu","orcid":"https://orcid.org/0000-0001-7910-810X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Liu","raw_affiliation_strings":["Youtu Lab, Tencent"],"affiliations":[{"raw_affiliation_string":"Youtu Lab, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054879013","display_name":"Ran Yi","orcid":"https://orcid.org/0000-0003-1858-3358"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Yi","raw_affiliation_strings":["Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024119845","display_name":"Siqi Kou","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Kou","raw_affiliation_strings":["Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101292093","display_name":"Haokun Zhu","orcid":"https://orcid.org/0009-0009-8014-2730"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haokun Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385692","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0001-9943-6020"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["Youtu Lab, Tencent"],"affiliations":[{"raw_affiliation_string":"Youtu Lab, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028731909","display_name":"Yabiao Wang","orcid":"https://orcid.org/0000-0002-6592-8411"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yabiao Wang","raw_affiliation_strings":["Youtu Lab, Tencent","Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Youtu Lab, Tencent","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023834700","display_name":"Chengjie Wang","orcid":"https://orcid.org/0000-0003-4216-8090"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjie Wang","raw_affiliation_strings":["Shanghai Jiao Tong University","Youtu Lab, Tencent"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Youtu Lab, Tencent","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084218062","display_name":"Lizhuang Ma","orcid":"https://orcid.org/0000-0003-1653-4341"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhuang Ma","raw_affiliation_strings":["Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.976,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.588886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":85,"max":89},"biblio":{"volume":null,"issue":null,"first_page":"2406","last_page":"2415"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks in Image Processing","score":0.9992,"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/T10775","display_name":"Generative Adversarial Networks in Image Processing","score":0.9992,"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/T11309","display_name":"Audio Signal Classification and Analysis","score":0.9712,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10515","display_name":"Role of Long Noncoding RNAs in Cancer and Development","score":0.9672,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.89837706},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6047612},{"id":"https://openalex.org/keywords/topic-modeling","display_name":"Topic Modeling","score":0.533712},{"id":"https://openalex.org/keywords/content-analysis","display_name":"Content Analysis","score":0.501503}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.89837706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.78773284},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6898233},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6047612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.54295605},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43450278},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3908795},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3250065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32405344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27104855},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1069276},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.00228","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2309.03729","pdf_url":"https://arxiv.org/pdf/2309.03729","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2309.03729","pdf_url":"https://arxiv.org/pdf/2309.03729","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.44,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"grants":[{"funder":"https://openalex.org/F4320316083","funder_display_name":"Tencent","award_id":null},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":null},{"funder":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities","award_id":null}],"datasets":[],"versions":[],"referenced_works_count":38,"referenced_works":["https://openalex.org/W2153288431","https://openalex.org/W2475287302","https://openalex.org/W2910601191","https://openalex.org/W2961310105","https://openalex.org/W2962770929","https://openalex.org/W2963675401","https://openalex.org/W2984648456","https://openalex.org/W2996690341","https://openalex.org/W2998257851","https://openalex.org/W3008814843","https://openalex.org/W3015906192","https://openalex.org/W3033085318","https://openalex.org/W3034241236","https://openalex.org/W3034855543","https://openalex.org/W3035574324","https://openalex.org/W3036167779","https://openalex.org/W3092915627","https://openalex.org/W3096831136","https://openalex.org/W3099088591","https://openalex.org/W3112543861","https://openalex.org/W3120254195","https://openalex.org/W3121370741","https://openalex.org/W3162926177","https://openalex.org/W3174480022","https://openalex.org/W3191805365","https://openalex.org/W3202913169","https://openalex.org/W3217030260","https://openalex.org/W4221144097","https://openalex.org/W4285598072","https://openalex.org/W4286611322","https://openalex.org/W4307076412","https://openalex.org/W4308614312","https://openalex.org/W4312857984","https://openalex.org/W4312933868","https://openalex.org/W4312938578","https://openalex.org/W4313142698","https://openalex.org/W845365781","https://openalex.org/W967544008"],"related_works":["https://openalex.org/W4395044357","https://openalex.org/W4387506531","https://openalex.org/W4380551139","https://openalex.org/W4365211920","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W3042518613","https://openalex.org/W3015304056","https://openalex.org/W3014948380","https://openalex.org/W2087346071"],"abstract_inverted_index":{"Training":[0],"a":[1,10,53,82,130,162],"generative":[2,37,188],"model":[3,19,60,93,156,189],"with":[4,61,86],"limited":[5,32],"number":[6],"of":[7,75,107,121,183],"samples":[8],"is":[9,30,101,112,199],"challenging":[11],"task.":[12],"Current":[13],"methods":[14],"primarily":[15],"rely":[16],"on":[17],"few-shot":[18,58,187],"adaption":[20,190],"to":[21,40,90,115,193],"train":[22],"the":[23,36,76,119,138,141,151,181],"network.":[24],"However,":[25],"in":[26,118,186],"scenarios":[27],"where":[28],"data":[29],"extremely":[31],"(less":[33],"than":[34,150],"10),":[35],"network":[38],"tends":[39],"overfit":[41],"and":[42,96,103,124,143,148,177],"suffers":[43],"from":[44,157],"content":[45,56,88,95],"degradation.":[46],"To":[47],"address":[48],"these":[49],"problems,":[50],"we":[51,80,128,160],"propose":[52,161],"novel":[54,131],"phasic":[55,83,87],"fusing":[57],"diffusion":[59,77],"directional":[62,132],"distribution":[63,133],"consistency":[64,134,139,170],"loss,":[65],"which":[66],"targets":[67],"different":[68],"learning":[69],"objectives":[70],"at":[71],"distinct":[72],"training":[73,84],"stages":[74],"model.":[78],"Specifically,":[79],"design":[81],"strategy":[85,166],"fusion":[89],"help":[91],"our":[92,155,184],"learn":[94,104],"style":[97,123],"information":[98],"when":[99,110],"t":[100,111],"large,":[102],"local":[105,125],"details":[106],"target":[108],"domain":[109,172],"small,":[113],"leading":[114],"an":[116],"improvement":[117],"capture":[120],"content,":[122],"details.":[126],"Furthermore,":[127],"introduce":[129],"loss":[135],"that":[136,167],"ensures":[137],"between":[140],"generated":[142],"source":[144,197],"distributions":[145],"more":[146],"efficiently":[147],"stably":[149],"prior":[152],"methods,":[153],"preventing":[154],"overfitting.":[158],"Finally,":[159],"cross-domain":[163],"structure":[164,169],"guidance":[165],"enhances":[168],"during":[171],"adaptation.":[173],"Theoretical":[174],"analysis,":[175],"qualitative":[176],"quantitative":[178],"experiments":[179],"demonstrate":[180],"superiority":[182],"approach":[185],"tasks":[191],"compared":[192],"state-of-the-art":[194],"methods.":[195],"The":[196],"code":[198],"available":[200],"at:":[201],"https://github.com/sjtuplayer/few-shot-diffusion.":[202]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4390873535","counts_by_year":[{"year":2024,"cited_by_count":3}],"updated_date":"2024-12-02T03:17:40.521757","created_date":"2024-01-16"}