{"id":"https://openalex.org/W7081966824","doi":"https://doi.org/10.1109/tcsvt.2025.3609410","title":"Exploring Pruning-Based Efficient Object Tracking via Hybrid Knowledge Distillation","display_name":"Exploring Pruning-Based Efficient Object Tracking via Hybrid Knowledge Distillation","publication_year":2025,"publication_date":"2025-09-12","ids":{"openalex":"https://openalex.org/W7081966824","doi":"https://doi.org/10.1109/tcsvt.2025.3609410"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2025.3609410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3609410","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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":null,"display_name":"Yidong Song","orcid":"https://orcid.org/0009-0001-2163-1085"},"institutions":[{"id":"https://openalex.org/I4210088176","display_name":"North West Agriculture and Forestry University","ror":null,"country_code":"CN","type":null,"lineage":["https://openalex.org/I4210088176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yidong Song","raw_affiliation_strings":["College of Information Engineering, Northwest A&F University, Yangling, China"],"raw_orcid":"https://orcid.org/0009-0001-2163-1085","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Northwest A&F University, Yangling, China","institution_ids":["https://openalex.org/I4210088176"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shilei Wang","orcid":"https://orcid.org/0000-0002-0507-7256"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilei Wang","raw_affiliation_strings":["School of Automation, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0507-7256","affiliations":[{"raw_affiliation_string":"School of Automation, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhaochuan Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088176","display_name":"North West Agriculture and Forestry University","ror":null,"country_code":"CN","type":null,"lineage":["https://openalex.org/I4210088176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaochuan Zeng","raw_affiliation_strings":["College of Information Engineering, Northwest A&F University, Yangling, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Northwest A&F University, Yangling, China","institution_ids":["https://openalex.org/I4210088176"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jikai Zheng","orcid":"https://orcid.org/0009-0005-7942-0167"},"institutions":[{"id":"https://openalex.org/I4210088176","display_name":"North West Agriculture and Forestry University","ror":null,"country_code":"CN","type":null,"lineage":["https://openalex.org/I4210088176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jikai Zheng","raw_affiliation_strings":["College of Information Engineering, Northwest A&F University, Yangling, China"],"raw_orcid":"https://orcid.org/0009-0005-7942-0167","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Northwest A&F University, Yangling, China","institution_ids":["https://openalex.org/I4210088176"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhenhua Wang","orcid":"https://orcid.org/0000-0001-5473-1499"},"institutions":[{"id":"https://openalex.org/I4210088176","display_name":"North West Agriculture and Forestry University","ror":null,"country_code":"CN","type":null,"lineage":["https://openalex.org/I4210088176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Wang","raw_affiliation_strings":["College of Information Engineering, Northwest A&F University, Yangling, China"],"raw_orcid":"https://orcid.org/0000-0001-5473-1499","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Northwest A&F University, Yangling, China","institution_ids":["https://openalex.org/I4210088176"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jifeng Ning","orcid":"https://orcid.org/0000-0002-7751-0936"},"institutions":[{"id":"https://openalex.org/I4210088176","display_name":"North West Agriculture and Forestry University","ror":null,"country_code":"CN","type":null,"lineage":["https://openalex.org/I4210088176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jifeng Ning","raw_affiliation_strings":["College of Information Engineering, Northwest A&F University, Yangling, China"],"raw_orcid":"https://orcid.org/0000-0002-7751-0936","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Northwest A&F University, Yangling, China","institution_ids":["https://openalex.org/I4210088176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210088176"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60680681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"2","first_page":"2433","last_page":"2448"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.673799991607666,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.673799991607666,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13067","display_name":"Geological Modeling and Analysis","score":0.030899999663233757,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14311","display_name":"Electrical and Electromagnetic Research","score":0.01720000058412552,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5587000250816345},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5572999715805054},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.5471000075340271},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.501800000667572},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5008000135421753},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4934999942779541},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.45750001072883606},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4431000053882599},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.44029998779296875},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4106000065803528}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8041999936103821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5792999863624573},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5587000250816345},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5572999715805054},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.5471000075340271},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.501800000667572},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.45750001072883606},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4106000065803528},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4020000100135803},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.392300009727478},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.3910999894142151},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.383899986743927},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35830000042915344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34630000591278076},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.32030001282691956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.29010000824928284},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27799999713897705},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2025.3609410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3609410","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3772607204","display_name":null,"funder_award_id":"62476227","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"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":59,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1857884451","https://openalex.org/W1861492603","https://openalex.org/W2408241409","https://openalex.org/W2518876086","https://openalex.org/W2557641257","https://openalex.org/W2605173812","https://openalex.org/W2750432752","https://openalex.org/W2794744029","https://openalex.org/W2891033863","https://openalex.org/W2898200825","https://openalex.org/W2962766617","https://openalex.org/W2963534981","https://openalex.org/W2966759264","https://openalex.org/W2997896013","https://openalex.org/W2998434318","https://openalex.org/W3001584168","https://openalex.org/W3035453691","https://openalex.org/W3035672751","https://openalex.org/W3090155371","https://openalex.org/W3167536469","https://openalex.org/W3173344965","https://openalex.org/W3176459575","https://openalex.org/W3181069167","https://openalex.org/W3203857058","https://openalex.org/W3212622989","https://openalex.org/W3214586131","https://openalex.org/W4214588794","https://openalex.org/W4214759957","https://openalex.org/W4236612852","https://openalex.org/W4296079497","https://openalex.org/W4312323989","https://openalex.org/W4312516520","https://openalex.org/W4312532041","https://openalex.org/W4312751983","https://openalex.org/W4312769570","https://openalex.org/W4312805142","https://openalex.org/W4312969002","https://openalex.org/W4313141028","https://openalex.org/W4313156423","https://openalex.org/W4313413160","https://openalex.org/W4319300771","https://openalex.org/W4320036892","https://openalex.org/W4321770555","https://openalex.org/W4386066081","https://openalex.org/W4386066311","https://openalex.org/W4386066459","https://openalex.org/W4387885793","https://openalex.org/W4390871892","https://openalex.org/W4391021637","https://openalex.org/W4392745231","https://openalex.org/W4393147957","https://openalex.org/W4394596949","https://openalex.org/W4402702990","https://openalex.org/W4402704627","https://openalex.org/W4402754169","https://openalex.org/W4402772396","https://openalex.org/W4404002839","https://openalex.org/W4413146294"],"related_works":[],"abstract_inverted_index":{"Transformer-based":[0],"trackers":[1],"have":[2],"demonstrated":[3],"remarkable":[4],"advancements":[5],"in":[6,210],"real-time":[7,205],"tracking":[8,51,71,92,222],"tasks":[9],"on":[10,224],"edge":[11],"devices.":[12],"Since":[13],"lightweight":[14],"backbone":[15,55],"networks":[16],"are":[17],"typically":[18],"designed":[19],"for":[20,91,140],"general-purpose":[21],"tasks,":[22],"our":[23],"analysis":[24],"reveals":[25],"that,":[26],"when":[27],"applied":[28],"to":[29,135,155,170],"target":[30],"tracking,":[31],"they":[32],"often":[33],"contain":[34],"structurally":[35],"redundant":[36],"layers,":[37],"which":[38,117],"limits":[39],"the":[40,75,147,190,202],"model\u2019s":[41],"efficiency.":[42],"To":[43],"address":[44],"this":[45],"issue,":[46],"we":[47,85,125,145,165],"propose":[48],"a":[49,87,97,195],"novel":[50],"framework":[52,89],"that":[53],"integrates":[54],"pruning":[56],"with":[57],"Hybrid":[58],"Knowledge":[59],"Distillation":[60,83],"(HKD),":[61],"effectively":[62],"reducing":[63,213],"model":[64,171,230],"parameters":[65],"and":[66,79,81,99,109,123,127,132,174,218,229],"FLOPs":[67],"while":[68,212],"preserving":[69],"high":[70],"accuracy.":[72],"Inspired":[73],"by":[74,150,208,216],"success":[76],"of":[77,104],"MiniLM":[78],"Focal":[80],"Global":[82,110,163],"(FGD),":[84],"design":[86],"HKD":[88,95],"tailored":[90],"tasks.":[93],"Our":[94,179],"introduces":[96],"multi-level":[98],"complementary":[100],"distillation":[101],"scheme,":[102],"consisting":[103],"Token":[105,113],"Distillation,":[106,108,114,144,164],"Local":[107,143],"Distillation.":[111],"In":[112,162],"unlike":[115],"MiniLM,":[116],"distills":[118],"attention":[119,138],"via":[120],"QK":[121],"dot-products":[122],"V,":[124],"disentangle":[126],"separately":[128],"distill":[129],"Q,":[130],"K,":[131],"V":[133],"representations":[134],"enhance":[136,175],"structural":[137],"alignment":[139],"tracking.":[141],"For":[142],"use":[146,166],"FGD":[148],"concept":[149],"incorporating":[151],"spatial":[152],"foreground-background":[153],"masks":[154],"capture":[156],"region-specific":[157],"discriminative":[158],"cues":[159],"more":[160],"effectively.":[161],"Vision":[167],"Mamba":[168],"module":[169],"long-range":[172],"dependencies":[173],"semantic-level":[176],"feature":[177],"alignment.":[178],"tracker":[180,206],"HKDT":[181],"achieves":[182],"state-of-the-art":[183],"(SOTA)":[184],"performance":[185],"across":[186],"multiple":[187],"datasets.":[188],"On":[189],"GOT-10k":[191],"benchmark,":[192],"it":[193],"demonstrates":[194],"groundbreaking":[196],"67.6%":[197],"Average":[198],"Overlap":[199],"(AO),":[200],"outperforming":[201],"current":[203],"SOTA":[204],"HiT-Base":[207],"3.6%":[209],"accuracy":[211],"computational":[214],"costs":[215],"64%":[217],"achieving":[219],"115%":[220],"faster":[221],"speed":[223],"CPU":[225],"platforms.":[226],"The":[227],"code":[228],"will":[231],"be":[232],"available":[233],"soon.":[234]},"counts_by_year":[],"updated_date":"2026-02-13T13:36:01.753593","created_date":"2025-10-10T00:00:00"}