4 citations · 5 across the 5 of their papers we have counts for
5 papers
Towards Unified Semantic and Controllable Image Fusion: A Diffusion Transformer Approach
Jiayang Li, Chengjie Jiang, Junjun Jiang +3
Image fusion aims to blend complementary information from multiple sensing modalities, yet existing approaches remain limited in robustness, adaptability, and controllability. Most…
ControlFusion: A Controllable Image Fusion Framework with Language-Vision Degradation Prompts
Linfeng Tang, Yeda Wang, Zhanchuan Cai +2
Current image fusion methods struggle to address the composite degradations encountered in real-world imaging scenarios and lack the flexibility to accommodate user-specific requir…
FM2S: Towards Spatially-Correlated Noise Modeling in Zero-Shot Fluorescence Microscopy Image Denoising
Jizhihui Liu, Qixun Teng, Qing Ma +1
Fluorescence microscopy image (FMI) denoising faces critical challenges due to the compound mixed Poisson-Gaussian noise with strong spatial correlation and the impracticality of a…
Fusion from Decomposition: A Self-Supervised Approach for Image Fusion and Beyond
Pengwei Liang, Junjun Jiang, Qing Ma +2
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…
MaeFuse: Transferring Omni Features with Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Training
Jiayang Li, Junjun Jiang, Pengwei Liang +2
In this paper, we introduce MaeFuse, a novel autoencoder model designed for Infrared and Visible Image Fusion (IVIF). The existing approaches for image fusion often rely on trainin…