Diffusion model with disentangled modulations for sharpening multispectral and hyperspectral images
The denoising diffusion model has received increasing attention in the field of image
generation in recent years, thanks to its powerful generation capability. However, diffusion …
generation in recent years, thanks to its powerful generation capability. However, diffusion …
CEFusion: An infrared and visible image fusion network based on cross-modal multi-granularity information interaction and edge guidance
B Yang, Y Hu, X Liu, J Li - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Infrared and visible image fusion (IVF) aims to generate a fused image with abundant texture
details and salient thermal radiation targets, which can not only preserve the necessary …
details and salient thermal radiation targets, which can not only preserve the necessary …
LFDT-Fusion: a latent feature-guided diffusion Transformer model for general image fusion
For image fusion tasks, it is inefficient for the diffusion model to iterate multiple times on the
original resolution image for feature map**. To address this issue, this paper proposes an …
original resolution image for feature map**. To address this issue, this paper proposes an …
SpectralDiff: A generative framework for hyperspectral image classification with diffusion models
Hyperspectral image (HSI) classification is an important issue in remote sensing field with
extensive applications in Earth science. In recent years, a large number of deep learning …
extensive applications in Earth science. In recent years, a large number of deep learning …
CFNet: An infrared and visible image compression fusion network
Image fusion aims to acquire a more complete image representation within a limited
physical space to more effectively support practical vision applications. Although the …
physical space to more effectively support practical vision applications. Although the …
DRMF: Degradation-robust multi-modal image fusion via composable diffusion prior
Existing multi-modal image fusion algorithms are typically designed for high-quality images
and fail to tackle degradation (eg, low light, low resolution, and noise), which restricts image …
and fail to tackle degradation (eg, low light, low resolution, and noise), which restricts image …
Diffusion policies for out-of-distribution generalization in offline reinforcement learning
Offline Reinforcement Learning (RL) methods leverage previous experiences to learn better
policies than the behavior policy used for data collection. However, they face challenges …
policies than the behavior policy used for data collection. However, they face challenges …
Pedestrian detection in low-light conditions: A comprehensive survey
Pedestrian detection remains a critical problem in various domains, such as computer
vision, surveillance, and autonomous driving. In particular, accurate and instant detection of …
vision, surveillance, and autonomous driving. In particular, accurate and instant detection of …
MMIF-INet: Multimodal medical image fusion by invertible network
D He, W Li, G Wang, Y Huang, S Liu - Information Fusion, 2025 - Elsevier
Multimodal medical image fusion (MMIF) technology aims to generate fused images that
comprehensively reflect the information of tissues, organs, and metabolism, thereby …
comprehensively reflect the information of tissues, organs, and metabolism, thereby …
FDiff-Fusion: Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation
In recent years, the denoising diffusion model has achieved remarkable success in image
segmentation modeling. With its powerful nonlinear modeling capabilities and superior …
segmentation modeling. With its powerful nonlinear modeling capabilities and superior …