Visible and infrared image fusion (VIF) has attracted a lot of interest in recent years due to its
application in many tasks, such as object detection, object tracking, scene segmentation …

Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …

It is very challenging for various visual tasks such as image fusion, pedestrian detection, and
image-to-image translation in low light conditions due to the loss of effective target areas. In …

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 …

Deep learning based fusion methods have been achieving promising performance in image
fusion tasks. This is attributed to the network architecture that plays a very important role in …

On-chip spectrometers with compact footprints are being extensively investigated owing to
their promising future in critical applications such as sensing, surveillance and spectral …

In this paper, we present a novel deep learning architecture for infrared and visible images
fusion problems. In contrast to conventional convolutional networks, our encoding network is …

In this paper, we present a systematic review and evaluation of existing single-image low-
light enhancement algorithms. Besides the commonly used low-level vision oriented …

Global terrorist threats and illegal migration have intensified concerns for the security of
citizens, and every effort is made to exploit all available technological advances to prevent …

With the advantage of high mobility, Unmanned Aerial Vehicles (UAVs) are used to fuel
numerous important applications in computer vision, delivering more efficiency and …