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 …

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 …

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 …

Integrating multiple different yet complementary feature representations has been proved to
be an effective way for boosting tracking performance. This paper investigates how to …

How to perform effective information fusion of different modalities is a core factor in boosting
the performance of RGBT tracking. This paper presents a novel deep fusion algorithm based …

We propose an end-to-end tracking framework for fusing the RGB and TIR modalities in
RGB-T tracking. Our baseline tracker is DiMP (Discriminative Model Prediction), which …

RGBT tracking becomes a popular computer vision task, and has a variety of applications in
visual surveillance systems, self-driving cars and intelligent transportation system. This …

Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …