{"id":"https://openalex.org/W3183152796","doi":"https://doi.org/10.1109/tmm.2022.3174341","title":"MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking","display_name":"MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking","publication_year":2022,"publication_date":"2022-05-11","ids":{"openalex":"https://openalex.org/W3183152796","doi":"https://doi.org/10.1109/tmm.2022.3174341","mag":"3183152796"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2022.3174341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3174341","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5100411426","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0001-6117-6745"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076167141","display_name":"Xiujun Shu","orcid":"https://orcid.org/0000-0002-5976-6022"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiujun Shu","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055433405","display_name":"Shiliang Zhang","orcid":"https://orcid.org/0000-0001-9053-9314"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiliang Zhang","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China","Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053609164","display_name":"Bo Jiang","orcid":"https://orcid.org/0000-0002-6238-1596"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631216","display_name":"Yaowei Wang","orcid":"https://orcid.org/0000-0003-2197-9038"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowei Wang","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023918894","display_name":"Yonghong Tian","orcid":"https://orcid.org/0000-0002-2978-5935"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghong Tian","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101596624","display_name":"Feng Wu","orcid":"https://orcid.org/0000-0003-1809-380X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wu","raw_affiliation_strings":["School of Information Science, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100411426"],"corresponding_institution_ids":["https://openalex.org/I4210136793"],"apc_list":null,"apc_paid":null,"fwci":5.9124,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.9727956,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"25","issue":null,"first_page":"4335","last_page":"4348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9957000017166138,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9941999912261963,"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/computer-science","display_name":"Computer science","score":0.8423909544944763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6932188868522644},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6079516410827637},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5772286653518677},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5578356385231018},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5144198536872864},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49741581082344055},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4710312485694885},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.46757131814956665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4358136057853699}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8423909544944763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6932188868522644},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6079516410827637},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5772286653518677},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5578356385231018},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5144198536872864},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49741581082344055},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4710312485694885},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.46757131814956665},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4358136057853699},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2022.3174341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3174341","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1048221617","display_name":null,"funder_award_id":"2108085Y23","funder_id":"https://openalex.org/F4320334897","funder_display_name":"Natural Science Foundation of Anhui Province"},{"id":"https://openalex.org/G2366631306","display_name":null,"funder_award_id":"62102205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3637388763","display_name":null,"funder_award_id":"U20B2052","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4587952244","display_name":null,"funder_award_id":"62027804","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6272629075","display_name":null,"funder_award_id":"62076004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6662223526","display_name":null,"funder_award_id":"61825101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8123053562","display_name":null,"funder_award_id":"2020M682828","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320334897","display_name":"Natural Science Foundation of Anhui Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":112,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1566601044","https://openalex.org/W1857884451","https://openalex.org/W2016802777","https://openalex.org/W2064675550","https://openalex.org/W2068723588","https://openalex.org/W2106944077","https://openalex.org/W2108598243","https://openalex.org/W2146502635","https://openalex.org/W2154889144","https://openalex.org/W2156137575","https://openalex.org/W2176137647","https://openalex.org/W2194775991","https://openalex.org/W2214012879","https://openalex.org/W2264178313","https://openalex.org/W2337890890","https://openalex.org/W2414711238","https://openalex.org/W2470394683","https://openalex.org/W2470648425","https://openalex.org/W2518013266","https://openalex.org/W2527415613","https://openalex.org/W2556867313","https://openalex.org/W2557641257","https://openalex.org/W2558899534","https://openalex.org/W2588503511","https://openalex.org/W2599547527","https://openalex.org/W2610871254","https://openalex.org/W2619847046","https://openalex.org/W2753789229","https://openalex.org/W2761592212","https://openalex.org/W2765667535","https://openalex.org/W2775609985","https://openalex.org/W2786111591","https://openalex.org/W2797812763","https://openalex.org/W2798857366","https://openalex.org/W2799148928","https://openalex.org/W2801375052","https://openalex.org/W2883108970","https://openalex.org/W2884585870","https://openalex.org/W2887522866","https://openalex.org/W2888456413","https://openalex.org/W2889260328","https://openalex.org/W2890223989","https://openalex.org/W2891969803","https://openalex.org/W2895230054","https://openalex.org/W2895906665","https://openalex.org/W2896228140","https://openalex.org/W2897436422","https://openalex.org/W2898200825","https://openalex.org/W2900474539","https://openalex.org/W2902535732","https://openalex.org/W2904531787","https://openalex.org/W2962778460","https://openalex.org/W2962824803","https://openalex.org/W2963121817","https://openalex.org/W2963139879","https://openalex.org/W2963188742","https://openalex.org/W2963471260","https://openalex.org/W2963499285","https://openalex.org/W2963685207","https://openalex.org/W2963873961","https://openalex.org/W2963905288","https://openalex.org/W2964038557","https://openalex.org/W2964111344","https://openalex.org/W2964423614","https://openalex.org/W2969626490","https://openalex.org/W2970971581","https://openalex.org/W2970995493","https://openalex.org/W2972392244","https://openalex.org/W2973058802","https://openalex.org/W2985459778","https://openalex.org/W2990187711","https://openalex.org/W2991778094","https://openalex.org/W2996575194","https://openalex.org/W2997131652","https://openalex.org/W3001584168","https://openalex.org/W3002567850","https://openalex.org/W3003423830","https://openalex.org/W3004943365","https://openalex.org/W3012425959","https://openalex.org/W3016355810","https://openalex.org/W3020910915","https://openalex.org/W3023203534","https://openalex.org/W3030006663","https://openalex.org/W3031667669","https://openalex.org/W3035020406","https://openalex.org/W3085887408","https://openalex.org/W3099166112","https://openalex.org/W3099681648","https://openalex.org/W3108235634","https://openalex.org/W3108822985","https://openalex.org/W3108986454","https://openalex.org/W3113146133","https://openalex.org/W3127152723","https://openalex.org/W3181069167","https://openalex.org/W3187310259","https://openalex.org/W3193488896","https://openalex.org/W3204554907","https://openalex.org/W3204647170","https://openalex.org/W4287556358","https://openalex.org/W4319990521","https://openalex.org/W4387587572","https://openalex.org/W6676161993","https://openalex.org/W6681435938","https://openalex.org/W6693305720","https://openalex.org/W6703477647","https://openalex.org/W6716109767","https://openalex.org/W6744170603","https://openalex.org/W6748011523","https://openalex.org/W6754805553","https://openalex.org/W6756015008","https://openalex.org/W6776640749"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W2951187577"],"abstract_inverted_index":{"Many":[0],"RGB-T":[1,199],"trackers":[2],"attempt":[3],"to":[4,33,94,138,158,184],"attain":[5],"robust":[6],"feature":[7,75,104,117,124,128],"representation":[8],"by":[9,43,108,149,166],"utilizing":[10],"an":[11],"adaptive":[12],"weighting":[13],"scheme":[14],"(or":[15],"attention":[16,173,192],"mechanism).":[17],"Different":[18],"from":[19],"these":[20,74],"works,":[21],"we":[22,62,72,156],"propose":[23,157],"a":[24,96,160,168],"new":[25,169],"dynamic":[26,79,97],"modality-aware":[27,80],"filter":[28],"generation":[29],"module":[30,137],"(named":[31],"MFGNet)":[32],"boost":[34],"the":[35,46,57,68,112,134,186,204],"message":[36],"communication":[37],"between":[38],"visible":[39,87,114],"and":[40,77,88,115,154,163,177],"thermal":[41,89,116],"data":[42],"adaptively":[44],"adjusting":[45],"convolutional":[47,98],"kernels":[48],"for":[49,142,189],"various":[50],"input":[51,103,123],"images":[52],"in":[53],"practical":[54],"tracking.":[55],"Given":[56],"image":[58],"pairs":[59],"as":[60],"input,":[61],"first":[63],"encode":[64],"their":[65,101],"features":[66,141],"with":[67,82,122],"backbone":[69],"network.":[70],"Then,":[71],"concatenate":[73],"maps":[76,105,118,129],"generate":[78,139],"filters":[81,90],"two":[83],"independent":[84],"networks.":[85],"The":[86,126,175],"will":[91,119,130],"be":[92,120,131],"used":[93,183],"conduct":[95,159],"operation":[99],"on":[100,196],"corresponding":[102],"respectively.":[106],"Inspired":[107],"residual":[109],"connection,":[110],"both":[111],"generated":[113],"summarized":[121],"maps.":[125],"augmented":[127],"fed":[132],"into":[133],"RoI":[135],"align":[136],"instance-level":[140],"subsequent":[143],"classification.":[144],"To":[145],"address":[146],"issues":[147],"caused":[148],"heavy":[150],"occlusion,":[151],"fast":[152],"motion":[153],"out-of-view,":[155],"joint":[161],"local":[162],"global":[164,191],"search":[165],"exploiting":[167],"direction-aware":[170,187],"target":[171],"driven":[172],"mechanism.":[174],"spatial":[176],"temporal":[178],"recurrent":[179],"neural":[180],"network":[181],"is":[182],"capture":[185],"context":[188],"accurate":[190],"prediction.":[193],"Extensive":[194],"experiments":[195],"three":[197],"large-scale":[198],"tracking":[200],"benchmark":[201],"datasets":[202],"validated":[203],"effectiveness":[205],"of":[206],"our":[207],"proposed":[208],"algorithm.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
