{"id":"https://openalex.org/W7123349107","doi":"https://doi.org/10.1109/cgip66596.2025.00018","title":"Deep Reinforcement Learning for Multiple Objects Tracking in Satellite Videos","display_name":"Deep Reinforcement Learning for Multiple Objects Tracking in Satellite Videos","publication_year":2025,"publication_date":"2025-07-11","ids":{"openalex":"https://openalex.org/W7123349107","doi":"https://doi.org/10.1109/cgip66596.2025.00018"},"language":"en","primary_location":{"id":"doi:10.1109/cgip66596.2025.00018","doi":"https://doi.org/10.1109/cgip66596.2025.00018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cgip66596.2025.00018","pdf_url":null,"source":{"id":"https://openalex.org/S7407087733","display_name":"International Conference on Computer Graphics and Image Processing (CGIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 3rd International Conference on Computer Graphics and Image Processing (CGIP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5058806422","display_name":"Qingyu Xu","orcid":"https://orcid.org/0000-0002-6980-6921","observed_orcids":["https://orcid.org/0000-0002-6980-6921"]},"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":"Qingyu Xu","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Science and Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Science and Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122858456","display_name":"Le Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Zhou","raw_affiliation_strings":["Information Engineering University,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University,Zhengzhou,China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074097342","display_name":"Weidong Sheng","orcid":"https://orcid.org/0000-0001-9287-8643","observed_orcids":["https://orcid.org/0000-0001-9287-8643"]},"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":"Weidong Sheng","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Science and Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Science and Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122856985","display_name":"Qianqian Zhang","orcid":null,"observed_orcids":[]},"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":"Qianqian Zhang","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Engineering,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Engineering,Hefei,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032382317","display_name":"Wei An","orcid":"https://orcid.org/0000-0001-8319-2105","observed_orcids":["https://orcid.org/0000-0001-8319-2105","https://orcid.org/0009-0002-1024-7536","https://orcid.org/0000-0003-2605-1749"]},"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":"Wei An","raw_affiliation_strings":["National University of Defense Technology,College of Electronic Science and Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Electronic Science and Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3612,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72978734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"56","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9916999936103821,"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":0.9916999936103821,"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/T11701","display_name":"Space Satellite Systems and Control","score":0.0017999999690800905,"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":0.0017000000225380063,"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/multiple-object-tracking","display_name":"multiple object tracking","score":0.9259999990463257},{"id":"https://openalex.org/keywords/satellite-video","display_name":"satellite video","score":0.8339999914169312},{"id":"https://openalex.org/keywords/deep-reinforcement-learning","display_name":"deep reinforcement learning","score":0.9330000281333923},{"id":"https://openalex.org/keywords/tracking-by-detection","display_name":"tracking-by-detection","score":0.8230000138282776},{"id":"https://openalex.org/keywords/multi-agent-reinforcement-learning","display_name":"multi-agent reinforcement learning","score":0.9810000061988831},{"id":"https://openalex.org/keywords/occlusion-handling","display_name":"occlusion handling","score":0.6940000057220459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7760000228881836},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.775600016117096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6851999759674072},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5882999897003174},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5861999988555908},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5591999888420105},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5530999898910522},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5378000140190125},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5264000296592712},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46639999747276306},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4546999931335449},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4438999891281128},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4316999912261963},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.35989999771118164},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3257000148296356},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3249000012874603},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cgip66596.2025.00018","doi":"https://doi.org/10.1109/cgip66596.2025.00018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cgip66596.2025.00018","pdf_url":null,"source":{"id":"https://openalex.org/S7407087733","display_name":"International Conference on Computer Graphics and Image Processing (CGIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 3rd International Conference on Computer Graphics and Image Processing (CGIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1531192956","https://openalex.org/W2056653303","https://openalex.org/W2252355370","https://openalex.org/W2508815980","https://openalex.org/W2603203130","https://openalex.org/W2738318237","https://openalex.org/W2780358087","https://openalex.org/W2894909756","https://openalex.org/W2919522067","https://openalex.org/W2920942303","https://openalex.org/W2991818340","https://openalex.org/W3030520226","https://openalex.org/W3084173793","https://openalex.org/W3095753995","https://openalex.org/W3165926952","https://openalex.org/W3183501258","https://openalex.org/W3207452968","https://openalex.org/W3210764906","https://openalex.org/W4221166276","https://openalex.org/W4286904999","https://openalex.org/W4310467366","https://openalex.org/W4315778389","https://openalex.org/W4319299988","https://openalex.org/W4380053227","https://openalex.org/W4386076204","https://openalex.org/W4390872732","https://openalex.org/W4396941327","https://openalex.org/W4399375585","https://openalex.org/W4400073319"],"related_works":["https://openalex.org/W7118580491","https://openalex.org/W4411948850","https://openalex.org/W4212841652","https://openalex.org/W4406693293","https://openalex.org/W4294311189","https://openalex.org/W4396611882","https://openalex.org/W4415481203","https://openalex.org/W4416294395","https://openalex.org/W4411605751","https://openalex.org/W4415743474"],"abstract_inverted_index":{"Although":[0],"deep":[1],"learning":[2,79],"has":[3],"been":[4],"widely":[5],"adopted":[6],"for":[7,128],"Multiple":[8],"Object":[9],"Tracking":[10,96],"in":[11,32,55,102,158],"Satellite":[12],"Videos":[13],"(SVMOT),":[14],"existing":[15],"methods":[16,157],"exhibit":[17],"a":[18,76,145],"fundamental":[19],"inconsistency:":[20],"they":[21],"treat":[22],"this":[23],"inherently":[24],"sequence-level":[25,77],"task":[26],"through":[27,87],"frame-level":[28],"training,":[29],"creating":[30],"mismatches":[31],"data":[33],"distribution":[34],"and":[35,40,67,125],"optimization":[36,93],"objectives":[37],"between":[38],"training":[39,84],"inference":[41,86],"phases.":[42],"Additionally,":[43],"tracking-by-detection":[44],"(TBD)":[45],"approaches":[46],"heavily":[47],"depend":[48],"on":[49,133,148],"object":[50,63,116],"detection":[51],"performance\u2014a":[52],"critical":[53],"bottleneck":[54],"satellite":[56,135],"videos":[57],"due":[58],"to":[59],"challenges":[60],"like":[61],"small":[62],"sizes,":[64],"low":[65],"resolution,":[66],"frequent":[68],"occlusions.":[69],"To":[70],"bridge":[71],"these":[72],"gaps,":[73],"we":[74],"propose":[75],"reinforcement":[78,104],"framework":[80],"that":[81],"directly":[82],"aligns":[83],"with":[85,150],"two":[88],"key":[89],"innovations:":[90],"(1)":[91],"Unified":[92],"using":[94],"Multi-Object":[95],"Accuracy":[97],"(MOTA)":[98],"as":[99,118],"non-differentiable":[100],"rewards":[101],"multi-agent":[103],"learning,":[105],"eliminating":[106],"approximation":[107],"requirements;":[108],"(2)":[109],"An":[110],"Agent-Transformer":[111],"architecture":[112],"where":[113],"each":[114],"tracked":[115],"acts":[117],"an":[119],"agent,":[120],"modeling":[121],"collaborative":[122],"inter-agent":[123],"interactions":[124],"environment":[126],"dynamics":[127],"globally":[129],"optimized":[130],"trajectories.":[131],"Evaluations":[132],"the":[134],"video":[136],"benchmark":[137],"VISO":[138,149],"demonstrate":[139],"our":[140],"method\u2019s":[141],"superior":[142],"performance,":[143],"achieving":[144],"52.5%":[146],"MOTA":[147],"5.1%":[151],"absolute":[152],"improvement":[153],"over":[154],"state-of-the-art":[155],"TBD":[156],"high-density":[159],"scenarios.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-01-14T00:00:00"}
