{"id":"https://openalex.org/W4223440058","doi":"https://doi.org/10.48550/arxiv.2204.04492","title":"S4OD: Semi-Supervised learning for Single-Stage Object Detection","display_name":"S4OD: Semi-Supervised learning for Single-Stage Object Detection","publication_year":2022,"publication_date":"2022-04-09","ids":{"openalex":"https://openalex.org/W4223440058","doi":"https://doi.org/10.48550/arxiv.2204.04492"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2204.04492","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.04492","pdf_url":"https://arxiv.org/pdf/2204.04492","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2204.04492","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101952039","display_name":"Yueming Zhang","orcid":"https://orcid.org/0000-0001-5866-7391"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yueming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076460510","display_name":"Xingxu Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Xingxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362891","display_name":"Chao Liu","orcid":"https://orcid.org/0000-0001-7363-1987"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352754","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0003-4813-2494"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036616000","display_name":"Xiaolin Song","orcid":"https://orcid.org/0000-0003-4625-2687"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Xiaolin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041232609","display_name":"Tengfei Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Tengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069960972","display_name":"Runbo Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Runbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041973254","display_name":"Hua Chai","orcid":"https://orcid.org/0000-0002-5236-7926"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chai, Hua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023321537","display_name":"Pengfei Xu","orcid":"https://orcid.org/0000-0001-9297-4336"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Pengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5021811730","display_name":"Guoshan Zhang","orcid":"https://orcid.org/0000-0003-0994-5468"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Guoshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.992900013923645,"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":0.992900013923645,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9811999797821045,"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/detector","display_name":"Detector","score":0.8620448112487793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6912185549736023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5937652587890625},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.5923476815223694},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5502241253852844},{"id":"https://openalex.org/keywords/single-stage","display_name":"Single stage","score":0.5447179079055786},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5411682724952698},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5205551385879517},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5164649486541748},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5030888915061951},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.44924280047416687},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4268849790096283},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22008007764816284},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17477792501449585},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08707985281944275},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07526788115501404},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.057154566049575806},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.054049134254455566}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.8620448112487793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6912185549736023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5937652587890625},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.5923476815223694},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5502241253852844},{"id":"https://openalex.org/C3020376581","wikidata":"https://www.wikidata.org/wiki/Q16866784","display_name":"Single stage","level":2,"score":0.5447179079055786},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5411682724952698},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5205551385879517},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5164649486541748},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5030888915061951},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.44924280047416687},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4268849790096283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22008007764816284},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17477792501449585},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08707985281944275},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07526788115501404},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.057154566049575806},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.054049134254455566},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2204.04492","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.04492","pdf_url":"https://arxiv.org/pdf/2204.04492","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2204.04492","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2204.04492","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2204.04492","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.04492","pdf_url":"https://arxiv.org/pdf/2204.04492","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2000775715","https://openalex.org/W2795393339","https://openalex.org/W4390618967","https://openalex.org/W3130163047","https://openalex.org/W2902329723","https://openalex.org/W2917343039","https://openalex.org/W3011325431"],"abstract_inverted_index":{"Single-stage":[0],"detectors":[1,10,19,41,53],"suffer":[2],"from":[3,127],"extreme":[4],"foreground-background":[5],"class":[6,45],"imbalance,":[7],"while":[8],"two-stage":[9,18],"do":[11],"not.":[12],"Therefore,":[13],"in":[14,76,103],"semi-supervised":[15],"object":[16],"detection,":[17],"can":[20,80],"deliver":[21],"remarkable":[22],"performance":[23],"by":[24],"only":[25,123],"selecting":[26],"high-quality":[27],"pseudo":[28,62,83,101],"labels":[29,63,84,102],"based":[30,117],"on":[31,118,134,140],"classification":[32,77],"scores.":[33],"However,":[34],"directly":[35],"applying":[36],"this":[37,66],"strategy":[38,75],"to":[39,55,85,95,110],"single-stage":[40,52,104],"would":[42],"aggravate":[43],"the":[44,97,112],"imbalance":[46],"with":[47],"fewer":[48],"positive":[49],"samples.":[50],"Thus,":[51],"have":[54],"consider":[56],"both":[57],"quality":[58,91,99],"and":[59,92,138],"quantity":[60],"of":[61,100,115],"simultaneously.":[64],"In":[65],"paper,":[67],"we":[68,106],"design":[69],"a":[70,108],"dynamic":[71],"self-adaptive":[72],"threshold":[73],"(DSAT)":[74],"branch,":[78],"which":[79],"automatically":[81],"select":[82],"achieve":[86],"an":[87],"optimal":[88],"trade-off":[89],"between":[90],"quantity.":[93],"Besides,":[94],"assess":[96],"regression":[98,113],"detectors,":[105],"propose":[107],"module":[109],"compute":[111],"uncertainty":[114],"boxes":[116],"Non-Maximum":[119],"Suppression.":[120],"By":[121],"leveraging":[122],"10%":[124],"labeled":[125],"data":[126],"COCO,":[128],"our":[129],"method":[130],"achieves":[131],"35.0%":[132],"AP":[133],"anchor-free":[135],"detector":[136,142],"(FCOS)":[137],"32.9%":[139],"anchor-based":[141],"(RetinaNet).":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
