Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116417
DC FieldValueLanguage
dc.contributorDepartment of Mechanical Engineeringen_US
dc.creatorZhang, Sen_US
dc.creatorZhang, Den_US
dc.creatorZou, Qen_US
dc.date.accessioned2025-12-23T07:58:58Z-
dc.date.available2025-12-23T07:58:58Z-
dc.identifier.issn0925-2312en_US
dc.identifier.urihttp://hdl.handle.net/10397/116417-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectAlternating token pruningen_US
dc.subjectRelevant attention similarityen_US
dc.subjectVisual trackingen_US
dc.titleATPTrack : visual tracking with alternating token pruning of dynamic templates and search regionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume625en_US
dc.identifier.doi10.1016/j.neucom.2025.129534en_US
dcterms.abstractConstantly varying appearance of targets brings tremendous challenges for visual object tracking, especially in long-term tracking and background interference scenarios. Current leading trackers attempt to introduce multi-level fixed and dynamic templates to encode changing target information and abundant spatiotemporal contexts. These methods achieve astonishing performance improvements. However, dynamic templates are obtained from intermediate frames with high tracking confidence scores. These frames are not manually annotated. Therefore, the accuracy of dynamic templates relies entirely on tracking results. Dynamic templates may contain a large amount of uninformative and irrelevant background noise due to imprecise tracking. Additionally, multiple templates result in increased computational complexity as well. In order to tackle the above problems, a novel tracker dubbed ATPTrack is proposed for efficient end-to-end tracking. ATPTrack combines the initial target information of fixed templates and updated target representations of dynamic templates. Particularly, ATPTrack develops an alternating token trimming method that prunes dynamic templates and search region progressively. After token simplification, target-related information is highlighted in both dynamic templates and search region, which makes it more computationally efficient. Furthermore, a novel similarity ranking module is incorporated into the dynamic template pruning (DTP) block and the search region pruning (SRP) block for selecting the most discriminative target tokens. The DTP and SRP blocks are responsible for efficient trimming of dynamic templates and the search region, separately. The proposed ATPTrack achieves competitive performance on multiple tracking benchmarks. Compared to merely trimming the search region, ATPTrack further reduces the multiply-accumulate operations (MACs) by 11.5 % with negligible performance drop of 0.3 % by alternately pruning dynamic templates and search region.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationNeurocomputing, 7 Apr. 2025, v. 625, 129534en_US
dcterms.isPartOfNeurocomputingen_US
dcterms.issued2025-04-07-
dc.identifier.scopus2-s2.0-85216894326-
dc.identifier.eissn1872-8286en_US
dc.identifier.artn129534en_US
dc.description.validate202512 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG000533/2025-12-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextFunding text 1: The authors would like to thank the financial support from the Research Institute for Artificial Intelligence of Things (RIAIoT), Research Institute for Advanced Manufacturing (RIAM), Research Institute for Intelligent Wearable Systems (RI-IWEAR), and Research Centre of Textiles for Future Fashion (RCTFF) at the Hong Kong Polytechnic University. The third author would like to acknowledge the financial support of the University Grants, College of Letters and Sciences-New Faculty Scholarship Support Program from Columbus State University.; Funding text 2: This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC); the York Research Chairs (YRC) program. The third author would like to acknowledge the financial support of the University Grants, College of Letters and Sciences-New Faculty Scholarship Support Program from Columbus State University.en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-04-07en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2027-04-07
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