{"id":"https://openalex.org/W4400067003","doi":"https://doi.org/10.1145/3663976.3664237","title":"SwapTrack: Enhancing RGB-T Tracking via Learning from Paired and Single-Modal Data","display_name":"SwapTrack: Enhancing RGB-T Tracking via Learning from Paired and Single-Modal Data","publication_year":2024,"publication_date":"2024-04-26","ids":{"openalex":"https://openalex.org/W4400067003","doi":"https://doi.org/10.1145/3663976.3664237"},"language":"en","primary_location":{"id":"doi:10.1145/3663976.3664237","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3663976.3664237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern Recognition","raw_type":"proceedings-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/A5099583379","display_name":"Jianyu Xie","orcid":"https://orcid.org/0009-0004-6053-4984"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianyu Xie","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China"],"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103233830","display_name":"Zhuo Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Zeng","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China"],"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103077314","display_name":"Zhijie Yang","orcid":"https://orcid.org/0009-0000-0259-1471"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijie Yang","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China"],"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027860035","display_name":"Junlin Zhou","orcid":"https://orcid.org/0000-0003-1717-6734"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junlin Zhou","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China"],"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103179504","display_name":"D. Roshni Bai","orcid":"https://orcid.org/0000-0002-9965-1158"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di Bai","raw_affiliation_strings":["Suining Municipal Government Services and Big Data Administration, China and Suining Institute of Digital Economy, China"],"affiliations":[{"raw_affiliation_string":"Suining Municipal Government Services and Big Data Administration, China and Suining Institute of Digital Economy, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029425733","display_name":"Duanbing Chen","orcid":"https://orcid.org/0000-0003-2239-3012"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Duanbing Chen","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China"],"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, China and Chengdu Union Big Data Technology Incorporation, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5099583379"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08761615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9970999956130981,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9969000220298767,"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":0.7290034890174866},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6113264560699463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.606551468372345},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5565544366836548},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5552018284797668},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5503536462783813},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11470726132392883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7290034890174866},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6113264560699463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.606551468372345},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5565544366836548},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5552018284797668},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5503536462783813},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11470726132392883},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3663976.3664237","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3663976.3664237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2527415613","https://openalex.org/W2783258213","https://openalex.org/W2794744029","https://openalex.org/W2898200825","https://openalex.org/W2963905288","https://openalex.org/W2998756268","https://openalex.org/W3023203534","https://openalex.org/W3046271476","https://openalex.org/W3090155371","https://openalex.org/W3099671582","https://openalex.org/W3101990647","https://openalex.org/W3105117126","https://openalex.org/W3105919488","https://openalex.org/W3138516171","https://openalex.org/W3158472981","https://openalex.org/W3171106688","https://openalex.org/W3172087149","https://openalex.org/W3176404283","https://openalex.org/W4226126595","https://openalex.org/W4283808043","https://openalex.org/W4386057714","https://openalex.org/W4386071994","https://openalex.org/W4386075603","https://openalex.org/W4386083135","https://openalex.org/W4387771700"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"RGB-T":[0,23,29,38,65,73],"tracking":[1,13],"leverages":[2],"the":[3,34,44,55,95,122,138,153,160],"complementary":[4],"information":[5],"from":[6,70,112],"both":[7,71],"RGB":[8,48],"and":[9,15,75,86,92,103,105,114],"thermal":[10],"modalities,":[11],"enhancing":[12],"robustness":[14],"accuracy":[16],"in":[17],"challenging":[18],"visual":[19],"conditions.":[20],"Most":[21],"existing":[22],"trackers":[24],"primarily":[25],"rely":[26],"on":[27],"paired":[28,37,72],"data":[30,74,116,158],"for":[31,99],"training.":[32],"However,":[33],"availability":[35],"of":[36,46,57,155],"images":[39],"is":[40],"limited":[41],"compared":[42],"to":[43,89,110],"abundance":[45],"single-modal":[47,76,113,148,157],"or":[49],"TIR":[50],"images.":[51],"To":[52],"fully":[53],"leverage":[54],"potential":[56],"all":[58],"available":[59],"data,":[60],"we":[61],"propose":[62],"SwapTrack,":[63],"an":[64],"tracker":[66],"that":[67,121,137],"effectively":[68],"learns":[69],"data.":[77,149],"The":[78],"proposed":[79,123,139],"approach":[80],"incorporates":[81],"three":[82],"key":[83],"designs:":[84],"shared":[85],"separated":[87],"networks":[88],"extract":[90],"modality-shared":[91],"modality-specific":[93],"patterns,":[94],"swapped":[96],"projection":[97],"network":[98],"modal":[100],"feature":[101],"conversion":[102],"complementation,":[104],"a":[106],"two-step":[107],"training":[108,161],"scheme":[109],"learn":[111],"multi-modal":[115],"effectively.":[117],"Experimental":[118],"results":[119],"demonstrate":[120],"method":[124,140],"outperforms":[125],"state-of-the-art":[126],"approaches":[127],"when":[128,145],"trained":[129],"with":[130],"RGB-T+RGB+TIR":[131],"datasets.":[132],"Furthermore,":[133],"ablation":[134],"studies":[135],"reveal":[136],"demonstrates":[141],"notable":[142],"performance":[143],"enhancements":[144],"introducing":[146],"additional":[147],"This":[150],"finding":[151],"underscores":[152],"effectiveness":[154],"incorporating":[156],"into":[159],"process.":[162]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}