Image fusion meets deep learning: A survey and perspective
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 …
from different source images, aims to generate a single image that is more informative and …
A review of multimodal image matching: Methods and applications
Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …
similar structure/content from two or more images that are of significant modalities or …
SwinFusion: Cross-domain long-range learning for general image fusion via swin transformer
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 …
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …
Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection
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 …
for object detection. Aiming at generating an image of high visual quality, previous …
SuperFusion: A versatile image registration and fusion network with semantic awareness
Image fusion aims to integrate complementary information in source images to synthesize a
fused image comprehensively characterizing the imaging scene. However, existing image …
fused image comprehensively characterizing the imaging scene. However, existing image …
PIAFusion: A progressive infrared and visible image fusion network based on illumination aware
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 …
targets and abundant texture details even under extreme illumination conditions. However …
Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network
Infrared and visible image fusion aims to synthesize a single fused image that not only
contains salient targets and abundant texture details but also facilitates high-level vision …
contains salient targets and abundant texture details but also facilitates high-level vision …
DIVFusion: Darkness-free infrared and visible image fusion
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 …
generate high-quality fused images with salient targets and abundant texture in extreme …
DDFM: denoising diffusion model for multi-modality image fusion
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 …
that retain the complementary features of each modality, such as functional highlights and …
RFN-Nest: An end-to-end residual fusion network for infrared and visible images
In the image fusion field, the design of deep learning-based fusion methods is far from
routine. It is invariably fusion-task specific and requires a careful consideration. The most …
routine. It is invariably fusion-task specific and requires a careful consideration. The most …