{"id":"https://openalex.org/W4410636489","doi":"https://doi.org/10.1145/3701716.3717653","title":"Hybrid, Unified and Iterative: A Novel Framework for Text-based Person Anomaly Retrieval","display_name":"Hybrid, Unified and Iterative: A Novel Framework for Text-based Person Anomaly Retrieval","publication_year":2025,"publication_date":"2025-05-08","ids":{"openalex":"https://openalex.org/W4410636489","doi":"https://doi.org/10.1145/3701716.3717653"},"language":"en","primary_location":{"id":"doi:10.1145/3701716.3717653","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3717653","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717653","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717653","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031473482","display_name":"Tien-Huy Nguyen","orcid":"https://orcid.org/0009-0000-0196-6083"},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Tien-Huy Nguyen","raw_affiliation_strings":["University of Information Technology Vietnam National University, Ho Chi Minh, Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Information Technology Vietnam National University, Ho Chi Minh, Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114223978","display_name":"Huu-Loc Tran","orcid":null},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huu-Loc Tran","raw_affiliation_strings":["University of Information Technology Vietnam National University, Ho Chi Minh, Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Information Technology Vietnam National University, Ho Chi Minh, Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093429050","display_name":"Huu-Phong Phan-Nguyen","orcid":"https://orcid.org/0009-0001-2243-7428"},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huu-Phong Phan-Nguyen","raw_affiliation_strings":["University of Information Technology Vietnam National University, Ho Chi Minh, Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Information Technology Vietnam National University, Ho Chi Minh, Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001592864","display_name":"Vinh Quang Dinh","orcid":"https://orcid.org/0000-0002-8025-2501"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quang-Vinh Dinh","raw_affiliation_strings":["AI VIETNAM Lab, Ninh Thuan, Vietnam"],"affiliations":[{"raw_affiliation_string":"AI VIETNAM Lab, Ninh Thuan, Vietnam","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031473482"],"corresponding_institution_ids":["https://openalex.org/I123565023"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20268931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1576","last_page":"1580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.957099974155426,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.957099974155426,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10751","display_name":"Forensic and Genetic Research","score":0.9473999738693237,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9332000017166138,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6839571595191956},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6093682050704956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42258352041244507},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41803693771362305},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34909293055534363},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07739949226379395}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6839571595191956},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6093682050704956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42258352041244507},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41803693771362305},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34909293055534363},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07739949226379395},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701716.3717653","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3717653","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717653","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3701716.3717653","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3717653","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717653","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410636489.pdf","grobid_xml":"https://content.openalex.org/works/W4410636489.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2883311563","https://openalex.org/W2894786240","https://openalex.org/W3152698349","https://openalex.org/W4312804044","https://openalex.org/W4313136445","https://openalex.org/W4387969466","https://openalex.org/W4389374124","https://openalex.org/W4402390102"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Text-based":[0],"person":[1],"anomaly":[2],"retrieval":[3],"has":[4],"emerged":[5],"as":[6],"a":[7,21,40,48,68,100,131,167],"challenging":[8],"task,":[9],"with":[10,47,163,166],"most":[11],"existing":[12],"approaches":[13],"relying":[14],"on":[15,137,159],"complex":[16],"deep-learning":[17],"techniques.":[18],"This":[19],"raises":[20],"research":[22],"question:":[23],"How":[24],"can":[25],"the":[26,55,122,126,143,149],"model":[27,72,111],"be":[28],"optimized":[29],"to":[30,53],"achieve":[31],"greater":[32],"fine-grained":[33,60],"features?":[34],"To":[35,118],"address":[36],"this,":[37,97],"we":[38,66,98,129],"propose":[39,99],"Local-Global":[41],"Hybrid":[42],"Perspective":[43],"(LHP)":[44],"module":[45],"integrated":[46],"Vision-Language":[49],"Model":[50],"(VLM),":[51],"designed":[52],"explore":[54],"effectiveness":[56,150],"of":[57,109,121,125,151],"incorporating":[58],"both":[59],"features":[61],"alongside":[62],"coarse-grained":[63],"features.":[64],"Additionally,":[65],"investigate":[67],"Unified":[69],"Image-Text":[70,80,83],"(UIT)":[71],"that":[73],"combines":[74],"multiple":[75],"objective":[76],"loss":[77],"functions,":[78],"including":[79],"Contrastive":[81],"(ITC),":[82],"Matching":[84],"(ITM),":[85],"Masked":[86,91],"Language":[87],"Modeling":[88,93],"(MLM),":[89],"and":[90,176],"Image":[92],"(MIM)":[94],"loss.":[95],"Beyond":[96],"novel":[101,132],"iterative":[102],"ensemble":[103,116],"strategy,":[104],"by":[105],"combining":[106],"iteratively":[107],"instead":[108],"using":[110],"results":[112],"simultaneously":[113],"like":[114],"other":[115],"methods.":[117],"take":[119],"advantage":[120],"superior":[123],"performance":[124,158],"LHP":[127],"model,":[128],"introduce":[130],"feature":[133],"selection":[134],"algorithm":[135],"based":[136],"its":[138],"guidance,":[139],"which":[140],"helps":[141],"improve":[142],"model's":[144],"performance.":[145],"Extensive":[146],"experiments":[147],"demonstrate":[148],"our":[152],"method":[153],"in":[154,170,174,179],"achieving":[155],"state-of-the-art":[156],"(SOTA)":[157],"PAB":[160],"dataset,":[161],"compared":[162],"previous":[164],"work,":[165],"9.70":[168],"improvement":[169,173,178],"R@1,":[171],"1.77":[172],"R@5,":[175],"1.01":[177],"R@10.":[180]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
