{"id":"https://openalex.org/W4378676984","doi":"https://doi.org/10.1145/3590003.3590089","title":"KRE: A Key-retained Random Erasing Method for Occluded Person Re-identification","display_name":"KRE: A Key-retained Random Erasing Method for Occluded Person Re-identification","publication_year":2023,"publication_date":"2023-03-17","ids":{"openalex":"https://openalex.org/W4378676984","doi":"https://doi.org/10.1145/3590003.3590089"},"language":"en","primary_location":{"id":"doi:10.1145/3590003.3590089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3590003.3590089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd 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/A5092045115","display_name":"Hongxia Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongxia Wang","raw_affiliation_strings":["School of Computer Science and Technology, Wuhan University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-8198-8855","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101903569","display_name":"Yao Ma","orcid":"https://orcid.org/0009-0008-5769-6949"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Ma","raw_affiliation_strings":["School of Computer Science and Technology, Wuhan University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0008-5769-6949","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100441915","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0002-1594-3488"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Chen","raw_affiliation_strings":["School of Computer Science and Technology, Wuhan University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-1594-3488","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Wuhan University of Technology, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092045115"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.3532,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57768004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"467","last_page":"473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9954000115394592,"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":0.7587299346923828},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6791225671768188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6613314747810364},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.5941576361656189},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5300896763801575},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5240737795829773},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5069808959960938},{"id":"https://openalex.org/keywords/random-noise","display_name":"Random noise","score":0.44819536805152893},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.428547739982605},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4179668724536896},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41324082016944885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41089940071105957},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3326954245567322},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18749794363975525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7587299346923828},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6791225671768188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6613314747810364},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.5941576361656189},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5300896763801575},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5240737795829773},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5069808959960938},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.44819536805152893},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.428547739982605},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4179668724536896},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41324082016944885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41089940071105957},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3326954245567322},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18749794363975525},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3590003.3590089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3590003.3590089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1949591461","https://openalex.org/W2099474347","https://openalex.org/W2204750386","https://openalex.org/W2235916736","https://openalex.org/W2795758732","https://openalex.org/W2798590501","https://openalex.org/W2895786668","https://openalex.org/W2931208564","https://openalex.org/W2962691289","https://openalex.org/W2962926870","https://openalex.org/W2963330186","https://openalex.org/W2963383990","https://openalex.org/W2963805953","https://openalex.org/W2963842104","https://openalex.org/W2964201641","https://openalex.org/W2964304299","https://openalex.org/W2967515867","https://openalex.org/W2981393440","https://openalex.org/W2988964414","https://openalex.org/W2998508940","https://openalex.org/W2998792609","https://openalex.org/W3034611771","https://openalex.org/W3035539956","https://openalex.org/W3100506510","https://openalex.org/W3161562489","https://openalex.org/W3174656328","https://openalex.org/W3175823695","https://openalex.org/W3177330184","https://openalex.org/W4214736485","https://openalex.org/W4312747676"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2347460059","https://openalex.org/W2111726165","https://openalex.org/W1984858032","https://openalex.org/W2616891703","https://openalex.org/W182104056"],"abstract_inverted_index":{"Occluded":[0],"person":[1,91,159],"re-identification":[2],"(ReID)":[3],"is":[4,35],"a":[5],"challenging":[6],"task":[7],"in":[8,21,31,87,106,149],"the":[9,15,18,38,45,54,59,62,84,95,101,118,122,130,138,142,146,157,163],"field":[10],"of":[11,37,61,121,129,141],"computer":[12],"vision,":[13],"facing":[14],"problem":[16],"that":[17,177],"target":[19],"pedestrians":[20],"probe":[22],"images":[23,88,143],"are":[24],"obscured":[25],"by":[26,144],"various":[27],"occlusions.":[28],"Random":[29,79,97,150],"Erasing":[30,80,151],"data":[32,74],"augmentation":[33,75],"techniques":[34],"one":[36],"effective":[39],"methods":[40,184],"used":[41],"to":[42,66,116,124],"deal":[43],"with":[44],"occlusion":[46],"problem,":[47,69],"but":[48],"it":[49],"may":[50],"introduce":[51,110],"noise":[52],"into":[53],"training":[55,60,131],"process,":[56,152],"which":[57,82,153],"affects":[58],"model.":[63],"In":[64],"order":[65],"solve":[67],"this":[68],"we":[70,99],"propose":[71],"an":[72,111],"novel":[73],"method":[76,115,165,179],"named":[77],"Key-retained":[78],"(KRE)":[81],"preserves":[83],"critical":[85],"parts":[86],"for":[89],"occluded":[90,158],"ReID.":[92],"Based":[93],"on":[94,166,185],"regular":[96],"Erasing,":[98],"utilize":[100],"naturally":[102],"generated":[103],"attention":[104],"map":[105],"Vision":[107],"Transformers":[108],"and":[109,169],"adaptive":[112],"threshold":[113],"selection":[114],"detect":[117],"key":[119,139,147],"areas":[120,148],"image":[123],"be":[125,134],"augmented.":[126],"The":[127],"complexity":[128],"samples":[132],"can":[133,154],"improved":[135],"without":[136],"losing":[137],"information":[140],"reserving":[145],"finally":[155],"alleviate":[156],"ReID":[160,171],"problem.":[161],"Validating":[162],"proposed":[164],"occluded,":[167],"partial":[168],"holistic":[170],"datasets,":[172],"extensive":[173],"experimental":[174],"results":[175],"demonstrate":[176],"our":[178],"performs":[180],"favorably":[181],"against":[182],"state-of-the-art":[183],"ViT-based":[186],"models.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}