Similarity has always been a key aspect in computer science and statistics. Any time two
element vectors are compared, many different similarity approaches can be used …

Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …

In the image fusion field, the design of deep learning-based fusion methods is far from
routine. It is invariably fusion-task specific and requires a careful consideration. The most …

We propose an online tracking algorithm that performs the object detection and data
association under a common framework, capable of linking objects after a long time span …

The perception of drones, also known as Unmanned Aerial Vehicles (UAVs), particularly in
infrared videos, is crucial for effective anti-UAV tasks. However, existing datasets for UAV …

Recent advances in deep networks have gained great attention in infrared and visible image
fusion (IVIF). Nevertheless, most existing methods are incapable of dealing with slight …

Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …

This work reviews the results of the NTIRE 2024 Challenge on Shadow Removal. Building
on the last year edition the current challenge was organized in two tracks with a track …

Abstract We present Siam R-CNN, a Siamese re-detection architecture which unleashes the
full power of two-stage object detection approaches for visual object tracking. We combine …

Siamese-based trackers have achieved excellent performance on visual object tracking.
However, the target template is not updated online, and the features of target template and …