{"id":"https://openalex.org/W7138284723","doi":"https://doi.org/10.1609/aaai.v40i5.37385","title":"Spatio-Temporal Context Learning with Temporal Difference Convolution for Moving Infrared Small Target Detection","display_name":"Spatio-Temporal Context Learning with Temporal Difference Convolution for Moving Infrared Small Target Detection","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138284723","doi":"https://doi.org/10.1609/aaai.v40i5.37385"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i5.37385","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37385","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37385/41347","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37385/41347","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032109527","display_name":"Houzhang Fang","orcid":"https://orcid.org/0000-0002-7949-8846"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houzhang Fang","raw_affiliation_strings":["Xidian University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007824412","display_name":"Shukai Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shukai Guo","raw_affiliation_strings":["Xidian University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023222077","display_name":"Q.Y. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuhuan Chen","raw_affiliation_strings":["Xidian University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129664677","display_name":"Yi Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Chang","raw_affiliation_strings":["Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129664039","display_name":"Luxin Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luxin Yan","raw_affiliation_strings":["Huazhong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":61.3249,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.99476039,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"40","issue":"5","first_page":"3840","last_page":"3848"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9101999998092651,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9101999998092651,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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":0.047200001776218414,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.00419999985024333,"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/leverage","display_name":"Leverage (statistics)","score":0.6328999996185303},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5976999998092651},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.5681999921798706},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5533000230789185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4625000059604645},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.44830000400543213},{"id":"https://openalex.org/keywords/temporal-difference-learning","display_name":"Temporal difference learning","score":0.43299999833106995},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.43130001425743103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480999827384949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6693000197410583},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6328999996185303},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5976999998092651},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.5681999921798706},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5533000230789185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.44830000400543213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.445499986410141},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.43299999833106995},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.43130001425743103},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.31679999828338623},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i5.37385","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37385","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37385/41347","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i5.37385","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37385","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37385/41347","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W7138284723.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Moving":[0,25],"infrared":[1,242,259],"small":[2],"target":[3,34,48,113,225,271],"detection":[4,175,267],"(IRSTD)":[5],"plays":[6],"a":[7,98,118,151,180,198,233],"critical":[8,224],"role":[9],"in":[10,71,170,269],"practical":[11],"applications,":[12],"such":[13],"as":[14],"surveillance":[15],"of":[16,86,239],"unmanned":[17],"aerial":[18],"vehicles":[19],"(UAVs)":[20],"and":[21,36,107,147,197,250,257],"UAV-based":[22],"search":[23],"system.":[24],"IRSTD":[26,101],"still":[27],"remains":[28],"highly":[29],"challenging":[30,235],"due":[31],"to":[32,133,209,219],"weak":[33],"features":[35,81,110,165,191],"complex":[37,171,251],"background":[38],"interference.":[39],"Accurate":[40],"spatio-temporal":[41,57,80,109,153,182,190],"feature":[42],"modeling":[43],"is":[44],"crucial":[45],"for":[46,111],"moving":[47,100,270],"detection,":[49],"typically":[50],"achieved":[51],"through":[52],"either":[53],"temporal":[54,91,120,139,145],"differences":[55],"or":[56],"(3D)":[58],"convolutions.":[59],"Temporal":[60],"difference":[61,121,146],"can":[62,159],"explicitly":[63],"leverage":[64],"motion":[65,87,163],"cues":[66],"but":[67],"exhibits":[68],"limited":[69],"capability":[70],"extracting":[72],"spatial":[73],"features,":[74,214],"whereas":[75],"3D":[76,148,200],"convolution":[77,122,149,154],"effectively":[78,105,160],"represents":[79],"yet":[82],"lacks":[83],"explicit":[84],"awareness":[85],"dynamics":[88],"along":[89],"the":[90,189,194,211,217],"dimension.":[92],"In":[93],"this":[94],"paper,":[95],"we":[96,116,178,231],"propose":[97,179],"novel":[99,119],"network":[102],"(TDCNet),":[103],"which":[104],"extracts":[106],"enhances":[108],"accurate":[112],"detection.":[114,272],"Specifically,":[115],"introduce":[117],"(TDC)":[123],"re-parameterization":[124],"module":[125,158],"that":[126,185,262],"comprises":[127],"three":[128],"parallel":[129,199],"TDC":[130,142],"blocks":[131],"designed":[132],"capture":[134,161],"contextual":[135,164],"dependencies":[136,208],"across":[137],"different":[138],"ranges.":[140],"Each":[141],"block":[143],"fuses":[144],"into":[150],"unified":[152],"representation.":[155],"This":[156,202],"re-parameterized":[157],"multi-scale":[162],"while":[166],"suppressing":[167],"pseudo-motion":[168],"clutter":[169],"backgrounds,":[172],"significantly":[173],"improving":[174],"performance.":[176],"Moreover,":[177],"TDC-guided":[181],"attention":[183],"mechanism":[184,203],"performs":[186],"cross-attention":[187],"between":[188],"extracted":[192],"from":[193],"TDC-based":[195],"backbone":[196],"backbone.":[201],"models":[204],"their":[205],"global":[206],"semantic":[207],"refine":[210],"current":[212],"frame\u2019s":[213],"thereby":[215],"guiding":[216],"model":[218],"focus":[220],"more":[221],"accurately":[222],"on":[223,255],"regions.":[226],"To":[227],"facilitate":[228],"comprehensive":[229],"evaluation,":[230],"construct":[232],"new":[234],"benchmark,":[236],"IRSTD-UAV,":[237],"consisting":[238],"15,106":[240],"real":[241],"images":[243],"with":[244],"diverse":[245],"low":[246],"signal-to-clutter":[247],"ratio":[248],"scenarios":[249],"backgrounds.":[252],"Extensive":[253],"experiments":[254],"IRSTD-UAV":[256],"public":[258],"datasets":[260],"demonstrate":[261],"our":[263],"TDCNet":[264],"achieves":[265],"state-of-the-art":[266],"performance":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-18T00:00:00"}
