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 …

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

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 …

The fusion of infrared and visible images aims to generate a composite image that can
simultaneously contain the thermal radiation information of an infrared image and the …

The end-to-end image fusion framework has achieved promising performance, with
dedicated convolutional networks aggregating the multi-modal local appearance. However …

Fusing infrared and visible images can provide more texture details for subsequent object
detection task. Conversely, detection task furnishes object semantic information to improve …

Infrared and visible light image fusion combines infrared and visible light images by
extracting the main information from each image and fusing it together to provide a more …

Visible and infrared image fusion is an important area in image processing due to its
numerous applications. While much progress has been made in recent years with efforts on …

Infrared and visible image fusion aims to obtain a synthetic image that can simultaneously
exhibit salient objects and provide abundant texture details. However, existing deep …

Infrared and visible image fusion aims to integrate comprehensive information from multiple
sources to achieve superior performances on various practical tasks, such as detection, over …