{"id":"https://openalex.org/W4415537029","doi":"https://doi.org/10.1145/3746027.3755807","title":"Prior-Free Augmentation for Cloth-Changing Person Re-Identification","display_name":"Prior-Free Augmentation for Cloth-Changing Person Re-Identification","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415537029","doi":"https://doi.org/10.1145/3746027.3755807"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755807","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd 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":null,"display_name":"Jiajun Zhang","orcid":"https://orcid.org/0009-0000-8405-1398"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiajun Zhang","raw_affiliation_strings":["South China University of Technology, Guangzhou, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0000-8405-1398","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100658181","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-1670-1368"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Pengcheng Laboratory, Shenzhen, Guangdong, China and Pazhou Lab (Huangpu), Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-1670-1368","affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory, Shenzhen, Guangdong, China and Pazhou Lab (Huangpu), Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101884230","display_name":"Si Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Si Wu","raw_affiliation_strings":["South China University of Technology, Guangzhou, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-9582-9193","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010277066","display_name":"Yong Xu","orcid":"https://orcid.org/0000-0001-7183-3155"},"institutions":[{"id":"https://openalex.org/I4210142539","display_name":"Guangdong Institute of Intelligent Manufacturing","ror":"https://ror.org/049jpjz09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210142539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xu","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis, South China University of Technology, Guangzhou, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-7183-3155","affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis, South China University of Technology, Guangzhou, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210142539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073082132","display_name":"Yaowei Wang","orcid":"https://orcid.org/0000-0002-6110-4036"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowei Wang","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-6110-4036","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong, China and Pengcheng Laboratory, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210136793"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.286311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10612","last_page":"10621"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T11448","display_name":"Face recognition and analysis","score":0.9976000189781189,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9555000066757202,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/clothing","display_name":"Clothing","score":0.6492999792098999},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.614300012588501},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5785999894142151},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5090000033378601},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4408000111579895},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4246000051498413},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4023999869823456},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3982999920845032},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3675000071525574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.678600013256073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6545000076293945},{"id":"https://openalex.org/C530175646","wikidata":"https://www.wikidata.org/wiki/Q11460","display_name":"Clothing","level":2,"score":0.6492999792098999},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.614300012588501},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5785999894142151},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5254999995231628},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5090000033378601},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4246000051498413},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4023999869823456},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3675000071525574},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34689998626708984},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3003000020980835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2818000018596649},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.2734000086784363},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26339998841285706},{"id":"https://openalex.org/C23746413","wikidata":"https://www.wikidata.org/wiki/Q1141379","display_name":"Seam carving","level":3,"score":0.251800000667572},{"id":"https://openalex.org/C543847140","wikidata":"https://www.wikidata.org/wiki/Q2642826","display_name":"Realism","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755807","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W3112897560","https://openalex.org/W3213696333","https://openalex.org/W4226211505","https://openalex.org/W4360884927","https://openalex.org/W4390231183"],"related_works":[],"abstract_inverted_index":{"Cloth-changing":[0,69],"Person":[1],"Re-Identification":[2],"(CCReID)":[3],"aims":[4],"to":[5,77,132],"recognize":[6],"individuals":[7],"across":[8],"clothing":[9,81,112],"variations":[10,82],"by":[11],"learning":[12],"clothing-invariant":[13,97],"representations.":[14],"However,":[15],"obtaining":[16],"sufficient":[17],"samples":[18],"of":[19],"the":[20],"same":[21],"person":[22,32,70],"in":[23,53],"diverse":[24],"outfits":[25],"is":[26],"often":[27],"impractical.":[28],"While":[29],"synthesizing":[30],"realistic":[31],"images":[33,79,156],"provides":[34],"an":[35],"effective":[36],"solution,":[37],"existing":[38],"augmentation":[39,159],"methods":[40],"require":[41],"labeled":[42],"data":[43],"and":[44,56,120,129,135,142],"external":[45,161],"priors":[46],"(e.g.,":[47],"pose":[48],"skeletons,":[49],"semantic":[50],"maps),":[51],"resulting":[52],"high":[54],"costs":[55],"limited":[57],"generalization.":[58],"To":[59],"this":[60],"end,":[61],"we":[62],"propose":[63],"a":[64,91,105,122],"Prior-Free":[65],"Augmentation":[66],"method":[67],"for":[68,157],"re-identification":[71],"(PFAC),":[72],"which":[73],"leverages":[74],"text":[75],"guidance":[76],"synthesize":[78],"with":[80,126],"while":[83],"maintaining":[84],"identity":[85,115],"consistency.":[86],"Our":[87],"approach":[88],"features:":[89],"(1)":[90],"truncated":[92],"diffusion":[93],"model":[94],"that":[95,109,146],"preserves":[96],"structural":[98],"cues":[99],"from":[100,114],"intermediate":[101],"noisy":[102],"images,":[103],"(2)":[104],"dual-branch":[106],"denoising":[107],"network":[108],"decouples":[110],"text-guided":[111],"synthesis":[113],"consistency":[116],"via":[117],"cross-modal":[118],"alignment,":[119],"(3)":[121],"joint":[123],"optimization":[124],"strategy":[125],"identity-focused":[127],"losses":[128],"image":[130],"filtering":[131],"enhance":[133],"realism":[134],"discriminability.":[136],"Experimental":[137],"results":[138],"on":[139],"PRCC,":[140],"LTCC,":[141],"Celeb-reID":[143],"datasets":[144],"demonstrate":[145],"PFAC":[147],"achieves":[148],"state-of-the-art":[149],"CCReID":[150],"performance,":[151],"effectively":[152],"generating":[153],"high-fidelity,":[154],"identity-consistent":[155],"robust":[158],"without":[160],"priors.":[162]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-25T00:00:00"}
