{"id":"https://openalex.org/W4416252043","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228181","title":"NP4Q: Nice Point for Post-training Quantization of Object Detection Models","display_name":"NP4Q: Nice Point for Post-training Quantization of Object Detection Models","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416252043","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228181"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5102635258","display_name":"Shunan Zhou","orcid":"https://orcid.org/0009-0006-4072-6799"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shunan Zhou","raw_affiliation_strings":["National University of Defense Technology,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer Science and Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047572387","display_name":"Jingfei Jiang","orcid":"https://orcid.org/0000-0003-2668-3228"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingfei Jiang","raw_affiliation_strings":["National University of Defense Technology,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer Science and Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691526","display_name":"Jiasheng Xu","orcid":"https://orcid.org/0000-0002-2055-8947"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Xu","raw_affiliation_strings":["National University of Defense Technology,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer Science and Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084283534","display_name":"Liangwei Li","orcid":"https://orcid.org/0009-0001-2658-1080"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangwei Li","raw_affiliation_strings":["National University of Defense Technology,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer Science and Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101923143","display_name":"Minghua Zhu","orcid":"https://orcid.org/0000-0002-6000-5837"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghua Zhu","raw_affiliation_strings":["National University of Defense Technology,College of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Computer Science and Technology","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102635258"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37555245,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8784000277519226,"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":0.8784000277519226,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.010400000028312206,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.010300000198185444,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/quantization","display_name":"Quantization (signal processing)","score":0.8234999775886536},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.6474999785423279},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.6284000277519226},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.597599983215332},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5593000054359436},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4968000054359436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4510999917984009}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.8234999775886536},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.6474999785423279},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.6284000277519226},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.597599983215332},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5302000045776367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5302000045776367},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4968000054359436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4510999917984009},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4187000095844269},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3889000117778778},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3386000096797943},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.26080000400543213}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":17,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2057954323","https://openalex.org/W2899818272","https://openalex.org/W2952122856","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2998218113","https://openalex.org/W3035219584","https://openalex.org/W3096609285","https://openalex.org/W3202442802","https://openalex.org/W4312757094","https://openalex.org/W4313069943","https://openalex.org/W4386075763","https://openalex.org/W4386076113","https://openalex.org/W4390873673","https://openalex.org/W4401567938"],"related_works":[],"abstract_inverted_index":{"Post-Training":[0],"Quantization":[1,156],"(PTQ)":[2],"methods":[3,31],"have":[4,36],"been":[5,37],"widely":[6],"applied":[7],"in":[8,49,66,102,198,215],"neural":[9],"network":[10],"model":[11,26],"compression":[12],"due":[13,52],"to":[14,17,46,53,128,160,209,213],"their":[15],"ability":[16],"compress":[18],"models":[19,35,42],"without":[20],"the":[21,25,54,61,97,123,130,138,150,153,163,166,186,191,205],"need":[22],"for":[23,32,149],"retraining":[24],"weights.":[27],"Recently,":[28],"various":[29],"quantization":[30,74,82,111,145],"object":[33,40,67],"detection":[34,41,68,192],"proposed.":[38],"Unfortunately,":[39],"are":[43],"highly":[44],"sensitive":[45],"quantization,":[47],"particularly":[48,197],"low-bit-width":[50],"scenarios,":[51],"high":[55],"dynamic":[56],"range":[57],"of":[58,64,165,194,207],"values.":[59],"Addressing":[60],"long-tailed":[62,91],"distribution":[63],"activations":[65,92,131],"models,":[69,196],"we":[70],"propose":[71],"NP4Q,":[72],"a":[73,78,103,109,117,141],"framework":[75],"that":[76,90,182],"employs":[77],"piecewise":[79,110],"non-uniform":[80],"clustering":[81],"method.":[83],"NP4Q":[84,107,114,173,183,203],"is":[85,146,158],"inspired":[86],"by":[87],"our":[88],"findings":[89],"can":[93,174],"be":[94],"characterized":[95],"using":[96,122],"mean":[98,124],"and":[99,125,134,171,189,211],"standard":[100,126],"deviation":[101,127],"similar":[104],"manner.":[105],"Consequently,":[106],"utilizes":[108],"strategy.":[112],"Specifically,":[113],"first":[115],"introduces":[116],"Nice":[118],"Boundary":[119],"Point":[120],"(NBP)":[121],"partition":[129],"into":[132],"head":[133,151],"tail":[135,139,188],"segments.":[136],"For":[137,201],"segment,":[140,152],"simple":[142],"MinMax":[143],"uniform":[144],"sufficient,":[147],"while":[148],"Meanshift":[154],"Clustering":[155],"(MCQ)":[157],"proposed":[159],"better":[161],"handle":[162],"majority":[164],"data.":[167],"By":[168],"leveraging":[169],"NBP":[170],"MCQ,":[172],"rapidly":[175],"generate":[176],"high-precision":[177],"quantized":[178,195],"models.":[179],"Experiments":[180],"demonstrate":[181],"effectively":[184],"segments":[185],"long":[187],"enhances":[190],"accuracy":[193,206],"low-bit":[199],"configurations.":[200],"instance,":[202],"pushes":[204],"YOLOv5s":[208],"52.2%":[210],"RetinaNet":[212],"35.3%":[214],"4-bit":[216],"INT.":[217]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
