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Found 6 papers, 0 papers with code
Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge.
Learning Cascaded Siamese Networks for High Performance Visual Tracking
In order to achieve high performance visual tracking in various negative scenarios, a novel cascaded Siamese network is proposed and developed based on two different deep learning networks: a matching subnetwork and a classification subnetwork.
Siamese Attentional Keypoint Network for High Performance Visual Tracking
In this paper, we investigate the impacts of three main aspects of visual tracking, i. e., the backbone network, the attentional mechanism, and the detection component, and propose a Siamese Attentional Keypoint Network, dubbed SATIN, for efficient tracking and accurate localization.
High Performance Visual Tracking with Circular and Structural Operators
Based on the proposed circular and structural operators, a set of primal confidence score maps can be obtained by circular correlating feature maps with their corresponding structural correlation filters.
A Complementary Tracking Model with Multiple Features
Discriminative Correlation Filters based tracking algorithms exploiting conventional handcrafted features have achieved impressive results both in terms of accuracy and robustness.
Large Margin Structured Convolution Operator for Thermal Infrared Object Tracking
To the best of our knowledge, we are the first to incorporate the advantages of DCF and SOSVM for TIR object tracking.
