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 current constraint rules of end-to-end infrared and visible image fusion (IVIF) networks
based on deep learning solely focus on the pixel level, disregarding the consideration of …

Target detection in high-contrast, multi-object images and movies is challenging. This
difficulty results from different areas and objects/people having varying pixel distributions …

Considering the prospects for image fusion, it is necessary to guide the fusion to adapt to
downstream vision tasks. In this paper, we propose an Adaptive Cross-Fusion Network …

Aiming at the problem of target detection for multiple source information fusion, in this article,
a decision-level fusion algorithm for visible and SAR images is proposed. First, using the …

To address the challenges of inadequate preservation of prominent targets, poor retention of
texture details, and unsatisfactory reconstruction of image backgrounds in image fusion. In …

In the task of infrared and visible image fusion, source images often exhibit complex and
variable characteristics due to scene illumination. To address the challenges posed by …

Enhancement of a low-contrast image is an essential and challenging task in any computer
vision-related application. Perceptually invisible images and the images captured by low …

To effectively preserve thermal targets in infrared (IR) images and texture information in
visible (VIS) images, this paper proposes a saliency detection-based and multi-scale …

Since the convolutional operation pays too much attention to local information, resulting in
the loss of global information and a decline in fusion quality. In order to ensure that the fused …