Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases
such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles …

Modern multi-object tracking (MOT) systems usually build trajectories through associating
per-frame detections. However, facing the challenges of camera motion, fast motion, and …

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 …

Unlike the visual object tracking, thermal infrared object tracking can track a target object in
total darkness. Therefore, it has broad applications, such as in rescue and video …

Existing deep Thermal InfraRed (TIR) trackers only use semantic features to represent the
TIR object, which lack the sufficient discriminative capacity for handling distractors. This …

Modern online multiple object tracking (MOT) methods usually focus on two directions to
improve tracking performance. One is to predict new positions in an incoming frame based …

Thermal infrared (TIR) pedestrian tracking is one of the important components among
numerous applications of computer vision, which has a major advantage: it can track …

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 …

Discriminative correlation filters (DCFs) have been widely used in the tracking community
recently. DCFs-based trackers utilize samples generated by circularly shifting from an image …

Using computational techniques especially deep learning methods to facilitate and enhance
cancer detection and diagnosis is a promising and important area. Nowadays, gene …