Recent advancements in the field of visual tracking have been propelled by the
amalgamation of Siamese networks and region proposal networks, which have …

Visual tracking is one of the most fundamental topics in computer vision. Numerous tracking
approaches based on discriminative correlation filters or Siamese convolutional networks …

Most thermal infrared (TIR) tracking methods are discriminative, treating the tracking
problem as a classification task. However, the objective of the classifier (label prediction) is …

Although numerous recent tracking approaches have made tremendous advances in the
last decade, achieving high-performance visual tracking remains a challenge. In this paper …

Abstract Convolution Neural Networks (CNNs) based trackers achieve excellent tracking
performance on tracking accuracy and speed. Feature extraction from the target template …

Multi-person pose estimation (MPPE) presents a challenging yet crucial task in computer
vision. Most existing methods predominantly concentrate on isolated interaction either …

Deep learning-based methods monopolize the latest research in the field of thermal infrared
(TIR) object tracking. However, relying solely on deep learning models to obtain better …

Abstract In recent years, Discriminative Correlation Filter (DCF) based tracking methods
have achieved impressive performance in visual tracking. However, their excellent …

Abstract Recently, Vision Transformer (ViT) has exhibited remarkable performances in many
computer vision tasks (eg object detection, segmentation and tracking). However, the output …

Addressing the core challenges of achieving both high efficiency and precision in UAV
tracking is crucial due to limitations in computing resources, battery capacity, and maximum …