{"id":"https://openalex.org/W7139925901","doi":"https://doi.org/10.1109/tip.2026.3674367","title":"Causality-Based Modality- and Platform-Invariant Representation Learning for Dynamic RGBT Tracking and a Benchmark","display_name":"Causality-Based Modality- and Platform-Invariant Representation Learning for Dynamic RGBT Tracking and a Benchmark","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7139925901","doi":"https://doi.org/10.1109/tip.2026.3674367","pmid":"https://pubmed.ncbi.nlm.nih.gov/41860913"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3674367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3674367","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5130238777","display_name":"Zhaodong Ding","orcid":null},"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":"Zhaodong Ding","raw_affiliation_strings":["School of Artificial Intelligence, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, and Anhui Provincial Key Laboratory of Security Artificial Intelligence, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0001-5642-7869","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, and Anhui Provincial Key Laboratory of Security Artificial Intelligence, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chenglong Li","orcid":"https://orcid.org/0000-0002-7233-2739"},"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":"Chenglong Li","raw_affiliation_strings":["School of Artificial Intelligence, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, and Anhui Provincial Key Laboratory of Security Artificial Intelligence, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-7233-2739","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, and Anhui Provincial Key Laboratory of Security Artificial Intelligence, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shengqing Miao","orcid":null},"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":"Shengqing Miao","raw_affiliation_strings":["School of Electronic Information Engineering, Anhui University, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jin Tang","orcid":"https://orcid.org/0000-0001-8375-3590"},"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":"Jin Tang","raw_affiliation_strings":["National Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-8375-3590","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38013593,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"3141","last_page":"3156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.21549999713897705,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.21549999713897705,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.0892999991774559,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.08839999884366989,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5263000130653381},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4918000102043152},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.45890000462532043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40630000829696655},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.35670000314712524},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.314300000667572},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3091999888420105}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6837999820709229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6790000200271606},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4918000102043152},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.45890000462532043},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43540000915527344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40630000829696655},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.35670000314712524},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.314300000667572},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30230000615119934},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2825999855995178},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2809000015258789},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.25060001015663147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3674367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3674367","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:41860913","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41860913","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7086993549","display_name":null,"funder_award_id":"No.62376004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G845944294","display_name":null,"funder_award_id":"62376004","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Each":[0],"sequence":[1],"in":[2,45,53],"existing":[3,61],"RGBT":[4,62,78,97,150,252],"tracking":[5,28,98,190],"datasets":[6],"is":[7,125],"typically":[8],"captured":[9],"from":[10,99],"a":[11,73,100,136,164,205,214,256,266],"single":[12],"platform":[13,215,227],"equipped":[14,39],"with":[15,40,265],"both":[16],"RGB":[17],"(visible":[18],"light)":[19],"and":[20,34,47,56,83,92,103,113,176,200,248,291],"TIR":[21],"(thermal":[22],"infrared)":[23],"sensors.":[24,42],"In":[25,152,242],"real-world":[26],"applications,":[27],"some":[29],"objects":[30],"requires":[31],"cross-platform":[32,82],"collaboration":[33],"these":[35,69],"platforms":[36,48],"might":[37],"be":[38],"different":[41],"However,":[43],"changes":[44,89,228],"modalities":[46,91],"may":[49],"cause":[50],"significant":[51],"variations":[52],"target":[54,212],"appearance":[55],"abrupt":[57,197],"position":[58,201],"shifts,":[59],"which":[60,218,260],"trackers":[63],"struggle":[64],"to":[65,127,143,154,172,183,188,209,222,234,244],"handle.":[66],"To":[67,192],"address":[68],"challenges,":[70],"we":[71,94,134,162,203,254],"define":[72],"new":[74],"task,":[75],"termed":[76],"dynamic":[77,88,96,149,251],"tracking,":[79,253],"focusing":[80],"on":[81,131,185,229,275],"modality-variant":[84],"scenarios.":[85],"Considering":[86],"the":[87,123,156,181,194,211,224,232,246,279,282],"of":[90,108,196,226,250,262,268,281],"platforms,":[93],"investigate":[95],"causal":[101,109,165],"perspective,":[102],"assume":[104],"that":[105,168],"images":[106],"consist":[107],"factors":[110,115],"(target-relevant":[111],"information)":[112],"non-causal":[114],"(target-irrelevant":[116],"information,":[117],"i.e.,":[118],"modality/platform":[119],"information),":[120],"where":[121],"only":[122],"former":[124],"conducive":[126],"stable":[128],"tracking.":[129,151],"Based":[130],"this":[132],"assumption,":[133],"propose":[135],"novel":[137],"causality-based":[138],"modality&platform-invariant":[139],"representation":[140],"learning":[141],"approach":[142],"capture":[144],"robust":[145],"invariant":[146],"representations":[147,237],"for":[148,238],"particular,":[153],"mitigate":[155],"challenges":[157],"posed":[158],"by":[159],"modality":[160],"variations,":[161,179],"design":[163,204],"consistency":[166],"encoder":[167],"introduces":[169],"an":[170,220],"intervener":[171,221],"model":[173,182],"feature":[174],"uncertainty":[175],"simulate":[177,223],"modal":[178],"compelling":[180],"focus":[184],"modality-invariant":[186],"features":[187],"improve":[189],"robustness.":[191],"overcome":[193],"issue":[195],"view":[198],"change":[199],"shift,":[202],"platform-independent":[206],"global":[207],"searcher":[208,233],"re-localize":[210],"whenever":[213],"switch":[216],"occurs,":[217],"leverages":[219],"interference":[225],"features,":[230],"encouraging":[231],"learn":[235],"platform-invariant":[236],"improved":[239],"localization":[240],"accuracy.":[241],"addition,":[243],"promote":[245],"research":[247],"development":[249],"construct":[255],"dataset":[257,277],"named":[258],"DRGBT603,":[259],"consists":[261],"603":[263],"sequences":[264],"total":[267],"1.49":[269],"M":[270],"frame":[271],"pairs.":[272],"Extensive":[273],"experiments":[274],"DRGBT603":[276],"validate":[278],"effectiveness":[280],"proposed":[283],"method":[284],"against":[285],"other":[286],"state-of-the-art":[287],"methods.":[288],"Our":[289],"code":[290],"data":[292],"are":[293],"now":[294],"available:":[295],"https://github.com/dongdong2061/DRGBT.":[296]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-21T00:00:00"}