The field of computer vision is revolutionized with the advancement of deep learning and the
availability of high computational power. In addition, in the field of computer vision, object …

The current Siamese network based on region proposal network (RPN) has attracted great
attention in visual tracking due to its excellent accuracy and high efficiency. However, the …

Object tracking belongs to active research areas in computer vision. We are interested in
matching-based trackers exploiting deep machine learning known as Siamese trackers …

In this article, we present a novel Siamese center-aware network (SiamCAN) for visual
tracking, which consists of the Siamese feature extraction subnetwork, followed by the …

The austere challenge of visual object tracking is to find the target to be tracked in various
noise interference and obtain its accurate bounding box coordinates. Recently, the object …

In this paper, we present a novel siamese motion-aware network (SiamMan) for visual
tracking, which consists of the siamese feature extraction subnetwork, followed by the …

In this paper, a tracking algorithm based on the residual neural network model and machine
learning is proposed. Compared with the widely used VGG network, the residual neural …

In order to solve the problems of unbalanced sample data and the lack of consideration of
temporal information in existing Siamese-based trackers, this paper proposes a Siamese …

摘要在计算机视觉领域中, 基于孪生网络的跟踪算法相比于传统算法提高了精度和速度,
但是仍会受到目标遮挡, 变形, 环境变化等影响, 导致孪生网络的跟踪算法的性能降低 …

Human key-point detection is a challenging research field in computer vision. Convolutional
neural models limit the number of parameters and mine the local structure, and have made …