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 …
Deep learning for hdr imaging: State-of-the-art and future trends
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range
of exposures, which is important in image processing, computer graphics, and computer …
of exposures, which is important in image processing, computer graphics, and computer …
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 …
HoLoCo: Holistic and local contrastive learning network for multi-exposure image fusion
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 …
exposures and generates a single higher dynamic image than each. Existing deep learning …
Transmef: A transformer-based multi-exposure image fusion framework using self-supervised multi-task learning
In this paper, we propose TransMEF, a transformer-based multi-exposure image fusion
framework that uses self-supervised multi-task learning. The framework is based on an …
framework that uses self-supervised multi-task learning. The framework is based on an …
Fusion from decomposition: A self-supervised decomposition approach for image fusion
Image fusion is famous as an alternative solution to generate one high-quality image from
multiple images in addition to image restoration from a single degraded image. The essence …
multiple images in addition to image restoration from a single degraded image. The essence …
Ghost-free high dynamic range imaging with context-aware transformer
High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …
Auto-exposure fusion for single-image shadow removal
Shadow removal is still a challenging task due to its inherent background-dependent and
spatial-variant properties, leading to unknown and diverse shadow patterns. Even powerful …
spatial-variant properties, leading to unknown and diverse shadow patterns. Even powerful …
ADNet: Attention-guided deformable convolutional network for high dynamic range imaging
In this paper, we present an attention-guided deformable convolutional network for hand-
held multi-frame high dynamic range (HDR) imaging, namely ADNet. This problem …
held multi-frame high dynamic range (HDR) imaging, namely ADNet. This problem …
SGFusion: A saliency guided deep-learning framework for pixel-level image fusion
Pixel-level image fusion, which merges different modal images into an informative image,
has attracted more and more attention. Despite many methods that have been proposed for …
has attracted more and more attention. Despite many methods that have been proposed for …