Matches in SemOpenAlex for { <https://semopenalex.org/work/W3205280353> ?p ?o ?g. }
- W3205280353 abstract "Recent object tracking methods depend upon deep networks or convoluted architectures. Most of those trackers can hardly meet real-time processing requirements on mobile platforms with limited computing resources. In this work, we introduce the Siamese Transformer Pyramid Network (SiamTPN), which inherits the advantages from both CNN and Transformer architectures. Specifically, we exploit the inherent feature pyramid of a lightweight network (ShuffleNetV2) and reinforce it with a Transformer to construct a robust target-specific appearance model. A centralized architecture with lateral cross attention is developed for building augmented high-level feature maps. To avoid the computation and memory intensity while fusing pyramid representations with the Transformer, we further introduce the pooling attention module, which significantly reduces memory and time complexity while improving the robustness. Comprehensive experiments on both aerial and prevalent tracking benchmarks achieve competitive results while operating at high speed, demonstrating the effectiveness of SiamTPN. Moreover, our fastest variant tracker operates over 30 Hz on a single CPU-core and obtaining an AUC score of 58.1% on the LaSOT dataset. Source codes are available at https://github.com/RISC-NYUAD/SiamTPNTracker" @default.
- W3205280353 created "2021-10-25" @default.
- W3205280353 creator A5040810487 @default.
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- W3205280353 date "2022-01-01" @default.
- W3205280353 modified "2023-10-11" @default.
- W3205280353 title "Siamese Transformer Pyramid Networks for Real-Time UAV Tracking" @default.
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- W3205280353 doi "https://doi.org/10.1109/wacv51458.2022.00196" @default.
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