This paper investigates how to integrate the complementary information from RGB and
thermal (RGB-T) sources for object tracking. We propose a novel Convolutional Neural …

Many RGB-T trackers attempt to attain robust feature representation by utilizing an adaptive
weighting scheme (or attention mechanism). Different from these works, we propose a new …

Motivated by our observations on RGB-T data that pattern correlations are high-frequently
recurred across modalities also along sequence frames, in this paper, we propose a cross …

Thermal sensors play an important role in intelligent transportation system. This paper
studies the problem of RGB and thermal (RGBT) tracking in challenging situations by …

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 …

Object tracking in RGB-thermal (RGB-T) videos is increasingly used in many fields due to
the all-weather and all-day working capability of the dual-modality imaging system, as well …

The task of RGBT tracking aims to take the complementary advantages from visible
spectrum and thermal infrared data to achieve robust visual tracking, and receives more and …

In recent years, RGBT tracking has become a hot topic in the field of visual tracking, and
made great progress. In this paper, we propose a novel Trident Fusion Network (TFNet) to …

Hierarchical deep features can provide multilevel abstractions of target objects, which play
an important role in target localization and classification. Determining how to effectively …

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 …