Transformers in single object tracking

dc.contributor.authorKugarajeevan, J
dc.contributor.authorKokul, T
dc.contributor.authorRamanan, A
dc.contributor.authorFernando, S
dc.date.accessioned2023-11-29T07:50:23Z
dc.date.available2023-11-29T07:50:23Z
dc.date.issued2023
dc.description.abstractSingle-object tracking is a well-known and challenging research topic in computer vision. Over the last two decades, numerous researchers have proposed various algorithms to solve this problem and achieved promising results. Recently, Transformer-based tracking approaches have ushered in a new era in single-object tracking by introducing new perspectives and achieving superior tracking robustness. In this paper, we conduct an in-depth literature analysis of Transformer tracking approaches by categorizing them into CNN-Transformer based trackers, Two-stream Two-stage fully-Transformer based trackers, and One-stream One-stage fully-Transformer based trackers. In addition, we conduct experimental evaluations to assess their tracking robustness and computational efficiency using publicly available benchmark datasets. Furthermore, we measure their performances on different tracking scenarios to identify their strengths and weaknesses in particular situations. Our survey provides insights into the underlying principles of Transformer tracking approaches, the challenges they encounter, and the future directions they may take.en_US
dc.identifier.citationKugarajeevan, J., Kokul, T., Ramanan, A., & Fernando, S. (2023). Transformers in Single Object Tracking: An Experimental Survey. IEEE Access, 11, 80297–80326. https://doi.org/10.1109/ACCESS.2023.3298440en_US
dc.identifier.databaseIEE Xploreen_US
dc.identifier.doi10.1109/ACCESS.2023.3298440en_US
dc.identifier.issn2169-3536en_US
dc.identifier.journalIEEE Accessen_US
dc.identifier.pgnos80297-80326en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/21788
dc.identifier.volume11en_US
dc.identifier.year2023en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectDeep learningen_US
dc.subjecttracking reviewen_US
dc.subjecttransformer trackingen_US
dc.subjectvision transformeren_US
dc.subjectvisual object trackingen_US
dc.titleTransformers in single object trackingen_US
dc.title.alternativean experimental surveyen_US
dc.typeArticle-Full-texten_US

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