Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387684265> ?p ?o ?g. }
- W4387684265 endingPage "107273" @default.
- W4387684265 startingPage "107273" @default.
- W4387684265 abstract "Recent years have witnessed the exciting performance of trackers based on Transformer. However, they usually separate the process of information extraction and integration, weakening the information interaction between the target and search region. In addition, they depend on traditional Transformer to model the long range dependency, which leads to a lack of focus on the primary information needed by high-accuracy trackers. In this paper, a sparse mixed attention aggregation model is proposed for robust tracking based on visible and thermal infrared images. To be specific, a backbone network composed of sparse mixed attention is designed to achieve information extraction and integration. This is helpful to obtain specific discriminative feature information and enhance their communication. To give full play to the complementary visible and thermal information, a confidence aware aggregation network is designed, which can learn the reliable confidence of visible and thermal branches. Finally, a corner-based localization head is introduced to estimate the target state. Extensive experiments on three large-scale multimodal tracking benchmarks demonstrate the superior tracking ability of the proposed tracker over other advanced trackers." @default.
- W4387684265 created "2023-10-17" @default.
- W4387684265 creator A5020462159 @default.
- W4387684265 creator A5084573070 @default.
- W4387684265 date "2024-01-01" @default.
- W4387684265 modified "2023-10-17" @default.
- W4387684265 title "Sparse mixed attention aggregation network for multimodal images fusion tracking" @default.
- W4387684265 cites W1857884451 @default.
- W4387684265 cites W2154889144 @default.
- W4387684265 cites W2214012879 @default.
- W4387684265 cites W2527415613 @default.
- W4387684265 cites W2765667535 @default.
- W4387684265 cites W2886910176 @default.
- W4387684265 cites W2896228140 @default.
- W4387684265 cites W2909946038 @default.
- W4387684265 cites W2945948323 @default.
- W4387684265 cites W2962766617 @default.
- W4387684265 cites W2963905288 @default.
- W4387684265 cites W2964423614 @default.
- W4387684265 cites W2969871771 @default.
- W4387684265 cites W2996575194 @default.
- W4387684265 cites W2997131652 @default.
- W4387684265 cites W2997248655 @default.
- W4387684265 cites W2998756268 @default.
- W4387684265 cites W3002567850 @default.
- W4387684265 cites W3005080107 @default.
- W4387684265 cites W3012425959 @default.
- W4387684265 cites W3035571898 @default.
- W4387684265 cites W3041551881 @default.
- W4387684265 cites W3064498204 @default.
- W4387684265 cites W3099681648 @default.
- W4387684265 cites W3103114094 @default.
- W4387684265 cites W3127317646 @default.
- W4387684265 cites W3132864630 @default.
- W4387684265 cites W3153607844 @default.
- W4387684265 cites W3157456624 @default.
- W4387684265 cites W3163754270 @default.
- W4387684265 cites W3171106688 @default.
- W4387684265 cites W3187284461 @default.
- W4387684265 cites W3196228261 @default.
- W4387684265 cites W3214116948 @default.
- W4387684265 cites W3214586131 @default.
- W4387684265 cites W4206998227 @default.
- W4387684265 cites W4214759957 @default.
- W4387684265 cites W4221067640 @default.
- W4387684265 cites W4224210628 @default.
- W4387684265 cites W4224235579 @default.
- W4387684265 cites W4226126595 @default.
- W4387684265 cites W4280526073 @default.
- W4387684265 cites W4312668764 @default.
- W4387684265 cites W4312805142 @default.
- W4387684265 cites W4313201440 @default.
- W4387684265 cites W4320036619 @default.
- W4387684265 cites W4322102230 @default.
- W4387684265 cites W4368351340 @default.
- W4387684265 cites W4380884766 @default.
- W4387684265 cites W4385155144 @default.
- W4387684265 doi "https://doi.org/10.1016/j.engappai.2023.107273" @default.
- W4387684265 hasPublicationYear "2024" @default.
- W4387684265 type Work @default.
- W4387684265 citedByCount "0" @default.
- W4387684265 crossrefType "journal-article" @default.
- W4387684265 hasAuthorship W4387684265A5020462159 @default.
- W4387684265 hasAuthorship W4387684265A5084573070 @default.
- W4387684265 hasConcept C121332964 @default.
- W4387684265 hasConcept C153180895 @default.
- W4387684265 hasConcept C154945302 @default.
- W4387684265 hasConcept C15744967 @default.
- W4387684265 hasConcept C165801399 @default.
- W4387684265 hasConcept C19417346 @default.
- W4387684265 hasConcept C2775936607 @default.
- W4387684265 hasConcept C31972630 @default.
- W4387684265 hasConcept C41008148 @default.
- W4387684265 hasConcept C52622490 @default.
- W4387684265 hasConcept C56461940 @default.
- W4387684265 hasConcept C57501372 @default.
- W4387684265 hasConcept C62520636 @default.
- W4387684265 hasConcept C66322947 @default.
- W4387684265 hasConcept C97931131 @default.
- W4387684265 hasConceptScore W4387684265C121332964 @default.
- W4387684265 hasConceptScore W4387684265C153180895 @default.
- W4387684265 hasConceptScore W4387684265C154945302 @default.
- W4387684265 hasConceptScore W4387684265C15744967 @default.
- W4387684265 hasConceptScore W4387684265C165801399 @default.
- W4387684265 hasConceptScore W4387684265C19417346 @default.
- W4387684265 hasConceptScore W4387684265C2775936607 @default.
- W4387684265 hasConceptScore W4387684265C31972630 @default.
- W4387684265 hasConceptScore W4387684265C41008148 @default.
- W4387684265 hasConceptScore W4387684265C52622490 @default.
- W4387684265 hasConceptScore W4387684265C56461940 @default.
- W4387684265 hasConceptScore W4387684265C57501372 @default.
- W4387684265 hasConceptScore W4387684265C62520636 @default.
- W4387684265 hasConceptScore W4387684265C66322947 @default.
- W4387684265 hasConceptScore W4387684265C97931131 @default.
- W4387684265 hasLocation W43876842651 @default.
- W4387684265 hasOpenAccess W4387684265 @default.
- W4387684265 hasPrimaryLocation W43876842651 @default.
- W4387684265 hasRelatedWork W1984282557 @default.