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 …

The images acquired by a single visible light sensor are very susceptible to light conditions,
weather changes, and other factors, while the images acquired by a single infrared light …

This study proposes a novel general image fusion framework based on cross-domain long-
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …

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 …

Infrared and visible image fusion aims to synthesize a single fused image containing salient
targets and abundant texture details even under extreme illumination conditions. However …

As a vital image enhancement technology, infrared and visible image fusion aims to
generate high-quality fused images with salient targets and abundant texture in extreme …

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 …

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 …