6 papers
Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Peng Gao, Qiquan Zhang, Fei Wang +3
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge. In this paper, we pro…
Learning Cascaded Siamese Networks for High Performance Visual Tracking
Peng Gao, Yipeng Ma, Ruyue Yuan +2
Visual tracking is one of the most challenging computer vision problems. In order to achieve high performance visual tracking in various negative scenarios, a novel cascaded Siames…
Siamese Attentional Keypoint Network for High Performance Visual Tracking
Peng Gao, Ruyue Yuan, Fei Wang +3
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…
High Performance Visual Tracking with Circular and Structural Operators
Peng Gao, Yipeng Ma, Ke Song +4
In this paper, a novel circular and structural operator tracker (CSOT) is proposed for high performance visual tracking, it not only possesses the powerful discriminative capabilit…
A Complementary Tracking Model with Multiple Features
Peng Gao, Yipeng Ma, Chao Li +3
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
Peng Gao, Yipeng Ma, Ke Song +3
Compared with visible object tracking, thermal infrared (TIR) object tracking can track an arbitrary target in total darkness since it cannot be influenced by illumination variatio…