Image fusion, which refers to extracting and then combining the most meaningful information
from different source images, aims to generate a single image that is more informative and …

Visual object tracking has attracted widespread interests recently. Due to the complementary
features provided by visible and infrared images, fusion tracking based on visible and …

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 …

Visible thermal person re-identification (VT-REID) is a task of matching person images
captured by thermal and visible cameras, which is an extremely important issue in night-time …

RGBT tracking receives a surge of interest in the computer vision community, but this
research field lacks a large-scale and high-diversity benchmark dataset, which is essential …

Abstract RGB-Thermal (RGB-T) object tracking receives more and more attention due to the
strongly complementary benefits of thermal information to visible data. However, RGB-T …

Stochastic gradient descent (SGD) is one of the core techniques behind the success of deep
neural networks. The gradient provides information on the direction in which a function has …

The development of a real-time and robust RGB-T tracker is an extremely challenging task
because the tracked object may suffer from shared and specific challenges in RGB and …

RGBT tracking has attracted increasing attention since RGB and thermal infrared data have
strong complementary advantages, which could make trackers all-day and all-weather work …

Face presentation attacks have become an increasingly critical concern when face
recognition is widely applied. Many face anti-spoofing methods have been proposed, but …