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 …

Multi-modality (MM) image fusion aims to render fused images that maintain the merits of
different modalities, eg, functional highlight and detailed textures. To tackle the challenge in …

Image fusion aims to integrate complementary information in source images to synthesize a
fused image comprehensively characterizing the imaging scene. However, existing image …

This study addresses the issue of fusing infrared and visible images that appear differently
for object detection. Aiming at generating an image of high visual quality, previous …

Multi-modality image fusion and segmentation play a vital role in autonomous driving and
robotic operation. Early efforts focus on boosting the performance for only one task, eg …

Multi-modality image fusion aims to combine different modalities to produce fused images
that retain the complementary features of each modality, such as functional highlights and …

The Metaverse, a transformative digital realm, holds immense promise for reshaping
industries and human interactions while potentially addressing global challenges and …

Multi-exposure image fusion (MEF) targets to integrate multiple shots with different
exposures and generates a single higher dynamic image than each. Existing deep learning …

Recent learning-based image fusion methods have marked numerous progress in pre-
registered multi-modality data, but suffered serious ghosts dealing with misaligned multi …

This research focuses on the discovery and localization of hidden objects in the wild and
serves unmanned systems. Through empirical analysis, infrared and visible image fusion …