Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …

Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

Tracking in the unmanned aerial vehicle (UAV) scenarios is one of the main components of
target-tracking tasks. Different from the target-tracking task in the general scenarios, the …

Siamese networks have drawn great attention in visual tracking because of their balanced
accuracy and speed. However, the backbone networks used in Siamese trackers are …

Raman optical spectroscopy promises label-free bacterial detection, identification, and
antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds …

Despite the numerous developments in object tracking, further development of current
tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data …

Existing deep trackers mainly use convolutional neural networks pre-trained for the generic
object recognition task for representations. Despite demonstrated successes for numerous …

Abstract Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from
unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to …