{"id":"https://openalex.org/W4288751081","doi":"https://doi.org/10.1109/tnnls.2022.3193614","title":"SPD: Semi-Supervised Learning and Progressive Distillation for 3-D Detection","display_name":"SPD: Semi-Supervised Learning and Progressive Distillation for 3-D Detection","publication_year":2022,"publication_date":"2022-07-29","ids":{"openalex":"https://openalex.org/W4288751081","doi":"https://doi.org/10.1109/tnnls.2022.3193614","pmid":"https://pubmed.ncbi.nlm.nih.gov/35905067"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3193614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3193614","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5026451492","display_name":"Bangquan Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Bangquan Xie","raw_affiliation_strings":["Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA","Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA; School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4500-8941","affiliations":[{"raw_affiliation_string":"Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA","institution_ids":["https://openalex.org/I8078737"]},{"raw_affiliation_string":"Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA; School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280","https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062081080","display_name":"Zongming Yang","orcid":"https://orcid.org/0000-0003-0876-7487"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zongming Yang","raw_affiliation_strings":["Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA"],"raw_orcid":"https://orcid.org/0000-0003-0876-7487","affiliations":[{"raw_affiliation_string":"Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101825563","display_name":"Liang Yang","orcid":"https://orcid.org/0000-0002-3454-6242"},"institutions":[{"id":"https://openalex.org/I4210153776","display_name":"Apple (United States)","ror":"https://ror.org/059hsda18","country_code":"US","type":"company","lineage":["https://openalex.org/I4210153776"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Yang","raw_affiliation_strings":["Apple Inc., Cupertino, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3454-6242","affiliations":[{"raw_affiliation_string":"Apple Inc., Cupertino, CA, USA","institution_ids":["https://openalex.org/I4210153776"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008479500","display_name":"Ruifa Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruifa Luo","raw_affiliation_strings":["Shenzhen Genvict Technologies Company Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Genvict Technologies Company Ltd., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100674628","display_name":"Jun L\u00fc","orcid":"https://orcid.org/0000-0003-0858-8577"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Lu","raw_affiliation_strings":["Shenzhen Genvict Technologies Company Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Genvict Technologies Company Ltd., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028860907","display_name":"Ailin Wei","orcid":"https://orcid.org/0000-0002-8626-3973"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ailin Wei","raw_affiliation_strings":["Department of Bioengineering, Clemson University, Clemson, SC, USA"],"raw_orcid":"https://orcid.org/0000-0002-8626-3973","affiliations":[{"raw_affiliation_string":"Department of Bioengineering, Clemson University, Clemson, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079266909","display_name":"Xiaoxiong Weng","orcid":"https://orcid.org/0000-0002-8215-8463"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxiong Weng","raw_affiliation_strings":["School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":null,"display_name":"Bing Li","orcid":"https://orcid.org/0000-0003-4987-6129"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA"],"raw_orcid":"https://orcid.org/0000-0003-4987-6129","affiliations":[{"raw_affiliation_string":"Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR), Greenville, SC, USA","institution_ids":["https://openalex.org/I8078737"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5873,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.65804527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"35","issue":"3","first_page":"3503","last_page":"3513"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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":0.9994000196456909,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9990000128746033,"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":0.9987999796867371,"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/distillation","display_name":"Distillation","score":0.5957146883010864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48357173800468445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4826357960700989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39725247025489807},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.20291155576705933},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.16244032979011536}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5957146883010864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48357173800468445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4826357960700989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39725247025489807},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.20291155576705933},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.16244032979011536}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3193614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3193614","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35905067","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35905067","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1690739335","https://openalex.org/W1821462560","https://openalex.org/W1923184257","https://openalex.org/W2145494108","https://openalex.org/W2148029428","https://openalex.org/W2294370754","https://openalex.org/W2468368736","https://openalex.org/W2493235117","https://openalex.org/W2561238782","https://openalex.org/W2594519801","https://openalex.org/W2780829839","https://openalex.org/W2798462325","https://openalex.org/W2887783173","https://openalex.org/W2904332125","https://openalex.org/W2936864631","https://openalex.org/W2949708697","https://openalex.org/W2951517617","https://openalex.org/W2951970475","https://openalex.org/W2952229419","https://openalex.org/W2953070460","https://openalex.org/W2963121255","https://openalex.org/W2963140444","https://openalex.org/W2964062501","https://openalex.org/W2964111476","https://openalex.org/W2982242214","https://openalex.org/W2986015886","https://openalex.org/W2988715931","https://openalex.org/W2997006708","https://openalex.org/W3017930107","https://openalex.org/W3034295752","https://openalex.org/W3034314779","https://openalex.org/W3034602892","https://openalex.org/W3035057392","https://openalex.org/W3044856323","https://openalex.org/W3053706811","https://openalex.org/W3088900620","https://openalex.org/W3092761163","https://openalex.org/W3107819843","https://openalex.org/W3113028524","https://openalex.org/W3116730076","https://openalex.org/W3117804044","https://openalex.org/W3131093608","https://openalex.org/W3134233478","https://openalex.org/W3166089996","https://openalex.org/W3178218920","https://openalex.org/W3209200209","https://openalex.org/W4288020585","https://openalex.org/W4293390340","https://openalex.org/W6623329352","https://openalex.org/W6637551013","https://openalex.org/W6691815588","https://openalex.org/W6730179637","https://openalex.org/W6733814495","https://openalex.org/W6765939562","https://openalex.org/W6770578729","https://openalex.org/W6779977557","https://openalex.org/W6781054486","https://openalex.org/W6781927018","https://openalex.org/W6783289990","https://openalex.org/W6803021174"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Current":[0],"learning-based":[1],"3-D":[2],"object":[3],"detection":[4,23],"accuracy":[5,24,292],"is":[6,14,198,228,268],"heavily":[7],"impacted":[8],"by":[9,77,141,154],"the":[10,32,72,78,84,96,101,106,112,116,122,133,142,151,155,163,169,175,185,189,195,212,220,223,226,235,262,281],"annotation":[11],"quality.":[12],"It":[13,149],"still":[15],"a":[16,42,203,252,290],"challenge":[17],"to":[18,60,70,110,201,280],"expect":[19],"an":[20],"overall":[21],"high":[22],"for":[25],"all":[26],"classes":[27],"under":[28],"different":[29],"scenarios":[30],"given":[31],"dataset":[33,244],"sparsity.":[34],"To":[35],"mitigate":[36],"this":[37,39],"challenge,":[38],"article":[40],"proposes":[41],"novel":[43],"method":[44],"called":[45],"semi-supervised":[46,54],"learning":[47,55],"and":[48,57,103,118,145,161,177,225,240,242,251,294,296],"progressive":[49,89],"distillation":[50,59,90],"(SPD),":[51],"which":[52,267],"uses":[53,66],"(SSL)":[56],"knowledge":[58],"improve":[61,111],"label":[62,186],"efficiency.":[63,187],"The":[64],"SPD":[65,257,288],"two":[67,137],"big":[68,107,123,164,191],"backbones":[69,85,138],"hand":[71],"unlabeled/labeled":[73],"input":[74,102],"data":[75,97,130,143,158,178,250],"augmented":[76,129],"periodic":[79],"IO":[80],"augmentation":[81,98],"(PA).":[82],"Then":[83],"are":[86,139,232],"compressed":[87],"using":[88,174,274],"(PD).":[91],"Precisely,":[92],"PA":[93,160,176],"periodically":[94],"shifts":[95],"operations":[99],"between":[100,222],"output":[104],"of":[105,115],"backbone,":[108],"aiming":[109],"network's":[113],"generalization":[114],"unseen":[117],"unlabeled":[119,157],"data.":[120,172],"Using":[121,246],"backbone":[124,165,192,285],"can":[125],"benefit":[126],"from":[127,159],"large-scale":[128,156],"better":[131],"than":[132,261],"small":[134,204],"one.":[135],"And":[136],"trained":[140,190],"scale":[144],"ratio-sensitive":[146],"loss":[147,179],"(data-loss).":[148],"solves":[150],"over-flat":[152],"caused":[153],"helps":[162],"prevent":[166],"overfitting":[167],"on":[168,234],"limited-scale":[170],"labeled":[171,249,277],"Hence,":[173],"during":[180],"SSL":[181],"training":[182],"dramatically":[183],"improves":[184],"Next,":[188],"set":[193],"as":[194,208,270],"teacher":[196,227],"CNN":[197,216],"progressively":[199],"distilled":[200],"obtain":[202],"student":[205,215,224],"model,":[206],"referenced":[207],"PD.":[209],"PD":[210],"mitigates":[211],"problem":[213],"that":[214],"performance":[217],"degrades":[218],"when":[219],"gap":[221],"oversized.":[229],"Extensive":[230],"experiments":[231],"conducted":[233],"indoor":[236],"datasets":[237],"SUN":[238],"RGB-D":[239],"ScanNetV2":[241],"outdoor":[243],"KITTI.":[245],"only":[247,275],"50%":[248],"27%":[253],"smaller":[254],"model":[255],"size,":[256],"performs":[258],"0.32":[259],"higher":[260],"fully":[263,283],"supervised":[264,284],"VoteNet":[265],"[1]":[266],"adopted":[269],"our":[271],"backbone.":[272],"Besides,":[273],"2%":[276],"data,":[278],"compared":[279],"other":[282],"PV-RCNN":[286],"[2],":[287],"accomplishes":[289],"similar":[291],"(84.1":[293],"84.83)":[295],"30%":[297],"less":[298],"inference":[299],"time.":[300]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
