{"id":"https://openalex.org/W4315750684","doi":"https://doi.org/10.1109/lra.2023.3236583","title":"Boosting UAV Tracking With Voxel-Based Trajectory-Aware Pre-Training","display_name":"Boosting UAV Tracking With Voxel-Based Trajectory-Aware Pre-Training","publication_year":2023,"publication_date":"2023-01-12","ids":{"openalex":"https://openalex.org/W4315750684","doi":"https://doi.org/10.1109/lra.2023.3236583"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2023.3236583","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/lra.2023.3236583","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-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/A5101819709","display_name":"Sihang Li","orcid":"https://orcid.org/0000-0003-3053-5770"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihang Li","raw_affiliation_strings":["School of Mechanical Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-3053-5770","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105268108","display_name":"Changhong Fu","orcid":"https://orcid.org/0000-0002-9897-6022"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhong Fu","raw_affiliation_strings":["School of Mechanical Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9897-6022","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047438553","display_name":"Kunhan Lu","orcid":"https://orcid.org/0000-0001-8421-0539"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunhan Lu","raw_affiliation_strings":["School of Mechanical Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8421-0539","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064430477","display_name":"Haobo Zuo","orcid":"https://orcid.org/0000-0002-1092-9716"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haobo Zuo","raw_affiliation_strings":["School of Mechanical Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1092-9716","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346324","display_name":"Yiming Li","orcid":"https://orcid.org/0000-0002-0157-6218"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiming Li","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-0157-6218","affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100699151","display_name":"Chen Feng","orcid":"https://orcid.org/0000-0003-3211-1576"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Feng","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-3211-1576","affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1228,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79386051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"8","issue":"2","first_page":"1133","last_page":"1140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9908999800682068,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9883000254631042,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7853062152862549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7243903279304504},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6065143942832947},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5011658668518066},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4975610077381134},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4882988929748535},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4725874364376068},{"id":"https://openalex.org/keywords/stereoscopy","display_name":"Stereoscopy","score":0.4188615083694458},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3302454650402069},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2532532811164856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7853062152862549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7243903279304504},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6065143942832947},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5011658668518066},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4975610077381134},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4882988929748535},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4725874364376068},{"id":"https://openalex.org/C126057942","wikidata":"https://www.wikidata.org/wiki/Q35158","display_name":"Stereoscopy","level":2,"score":0.4188615083694458},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3302454650402069},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2532532811164856},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2023.3236583","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/lra.2023.3236583","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G468934012","display_name":null,"funder_award_id":"62173249","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8500223103","display_name":null,"funder_award_id":"20ZR1460100","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2470394683","https://openalex.org/W2518013266","https://openalex.org/W2518876086","https://openalex.org/W2592463526","https://openalex.org/W2599547527","https://openalex.org/W2609883120","https://openalex.org/W2776035257","https://openalex.org/W2778130973","https://openalex.org/W2798842862","https://openalex.org/W2886910176","https://openalex.org/W2898200825","https://openalex.org/W2927438889","https://openalex.org/W2963030525","https://openalex.org/W2963436578","https://openalex.org/W2963534981","https://openalex.org/W2964069521","https://openalex.org/W2968257580","https://openalex.org/W3003412316","https://openalex.org/W3035466700","https://openalex.org/W3035511673","https://openalex.org/W3096609285","https://openalex.org/W3108519869","https://openalex.org/W3138516171","https://openalex.org/W3167536469","https://openalex.org/W3168663926","https://openalex.org/W3169909246","https://openalex.org/W3170841864","https://openalex.org/W3174225630","https://openalex.org/W3179950005","https://openalex.org/W3203510176","https://openalex.org/W3204801262","https://openalex.org/W3207718618","https://openalex.org/W4200150166","https://openalex.org/W4214759957","https://openalex.org/W4385245566","https://openalex.org/W4385364879","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1578117154","https://openalex.org/W2385949326","https://openalex.org/W2789220062","https://openalex.org/W2542256560","https://openalex.org/W2534746541","https://openalex.org/W35704881","https://openalex.org/W1487175407","https://openalex.org/W2068395580","https://openalex.org/W2146154945","https://openalex.org/W2612376223"],"abstract_inverted_index":{"Siamese":[0],"network-based":[1],"object":[2,34],"tracking":[3,19,167],"has":[4],"remarkably":[5],"promoted":[6],"the":[7,17,39,50,75,94,97,120,130,144,148,161,181],"automatic":[8],"capability":[9,95,145],"for":[10,78],"highly-maneuvered":[11],"unmanned":[12],"aerial":[13],"vehicles":[14],"(UAVs).":[15],"However,":[16],"leading-edge":[18],"framework":[20,71],"often":[21],"depends":[22],"on":[23,154],"template":[24],"matching,":[25],"making":[26],"it":[27],"trapped":[28],"when":[29],"facing":[30],"multiple":[31],"views":[32],"of":[33,96,146,183],"in":[35,56,169,176],"consecutive":[36],"frames.":[37],"Moreover,":[38],"general":[40],"image-level":[41],"pretrained":[42],"backbone":[43,98],"can":[44],"overfit":[45],"to":[46,52,72,99,118],"holistic":[47],"representations,":[48],"causing":[49],"misalignment":[51],"learn":[53],"object-level":[54],"properties":[55],"UAV":[57,79,156,166],"tracking.":[58,80],"To":[59],"tackle":[60],"these":[61],"issues,":[62],"this":[63],"work":[64],"presents":[65],"<italic":[66],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[67],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">TRTrack</i>,":[68],"a":[69,82,135],"comprehensive":[70],"fully":[73,179],"exploit":[74],"stereoscopic":[76,101],"representation":[77],"Specifically,":[81],"novel":[83,136],"pre-training":[84],"paradigm":[85],"method":[86],"is":[87,104,116],"proposed.":[88],"Through":[89],"trajectory-aware":[90],"reconstruction":[91],"training":[92],"(TRT),":[93],"extract":[100],"structure":[102,126],"feature":[103],"strengthened":[105],"without":[106],"any":[107],"parameter":[108],"increment.":[109],"Accordingly,":[110],"an":[111],"innovative":[112],"hierarchical":[113],"self-attention":[114],"Transformer":[115],"proposed":[117,134,162],"capture":[119],"local":[121],"detail":[122],"information":[123],"and":[124,172],"global":[125],"knowledge.":[127],"For":[128],"optimizing":[129],"correlation":[131,138],"map,":[132],"we":[133],"spatial":[137,150],"refinement":[139],"(SCR)":[140],"module,":[141],"which":[142],"promotes":[143],"modeling":[147],"long-range":[149],"dependencies.":[151],"Comprehensive":[152],"experiments":[153],"three":[155],"challenging":[157],"benchmarks":[158],"demonstrate":[159],"that":[160],"TRTrack":[163],"achieves":[164],"superior":[165],"performance":[168],"both":[170],"precision":[171],"efficiency.":[173],"Quantitative":[174],"tests":[175],"real-world":[177],"settings":[178],"prove":[180],"effectiveness":[182],"our":[184],"work.":[185]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}