Coconet: Coupled contrastive learning network with multi-level feature ensemble for multi-modality image fusion
Infrared and visible image fusion targets to provide an informative image by combining
complementary information from different sensors. Existing learning-based fusion …
complementary information from different sensors. Existing learning-based fusion …
Text-IF: Leveraging Semantic Text Guidance for Degradation-Aware and Interactive Image Fusion
Image fusion aims to combine information from different source images to create a
comprehensively representative image. Existing fusion methods are typically helpless in …
comprehensively representative image. Existing fusion methods are typically helpless in …
Equivariant multi-modality image fusion
Multi-modality image fusion is a technique that combines information from different sensors
or modalities enabling the fused image to retain complementary features from each modality …
or modalities enabling the fused image to retain complementary features from each modality …
A task-guided, implicitly-searched and metainitialized deep model for image fusion
Image fusion plays a key role in a variety of multi-sensor-based vision systems, especially
for enhancing visual quality and/or extracting aggregated features for perception. However …
for enhancing visual quality and/or extracting aggregated features for perception. However …
Hybrid-supervised dual-search: Leveraging automatic learning for loss-free multi-exposure image fusion
Multi-exposure image fusion (MEF) has emerged as a prominent solution to address the
limitations of digital imaging in representing varied exposure levels. Despite its …
limitations of digital imaging in representing varied exposure levels. Despite its …
Depth Information Assisted Collaborative Mutual Promotion Network for Single Image Dehazing
Y Zhang, S Zhou, H Li - … of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
Recovering a clear image from a single hazy image is an open inverse problem. Although
significant research progress has been made most existing methods ignore the effect that …
significant research progress has been made most existing methods ignore the effect that …
Zero-Sharpen: A universal pansharpening method across satellites for reducing scale-variance gap via zero-shot variation
Pansharpening is a technique that combines a high-resolution panchromatic image
(HRPAN) and a low-resolution multi-spectral image (LRMS) to generate a high-resolution …
(HRPAN) and a low-resolution multi-spectral image (LRMS) to generate a high-resolution …
Residual spatial fusion network for rgb-thermal semantic segmentation
P Li, J Chen, B Lin, X Xu - Neurocomputing, 2024 - Elsevier
Semantic segmentation plays an important role in widespread applications such as
autonomous driving and robotic sensing. This work focuses on RGB-Thermal (RGB-T) …
autonomous driving and robotic sensing. This work focuses on RGB-Thermal (RGB-T) …
MPCFusion: Multi-scale parallel cross fusion for infrared and visible images via convolution and vision Transformer
The image fusion community is thriving with the wave of deep learning, and the most
popular fusion methods are usually built upon well-designed network structures. However …
popular fusion methods are usually built upon well-designed network structures. However …
Camf: An interpretable infrared and visible image fusion network based on class activation mapping
Image fusion aims to integrate the complementary information of source images and
synthesize a single fused image. Existing image fusion algorithms apply hand-crafted fusion …
synthesize a single fused image. Existing image fusion algorithms apply hand-crafted fusion …