48 citations · 76 across the 6 of their papers we have counts for
8 papers
-PnP: Plug-and-Play Denoising for Scientific Imaging with Self-Supervised Score Priors
Yukun Cui, Jiangshe Zhang, Shuang Xu +6
Modern image restoration methods increasingly rely on large-scale supervised training, yet clean targets are often prohibitively difficult to obtain in scientific imaging modalitie…
MambaVF: State Space Model for Efficient Video Fusion
Zixiang Zhao, Yukun Cui, Lilun Deng +4
Video fusion aims to integrate complementary information from multiple source videos while preserving temporal consistency. Effective modeling of temporal dynamics is essential to…
A Unified Solution to Video Fusion: From Multi-Frame Learning to Benchmarking
Zixiang Zhao, Haowen Bai, Bingxin Ke +5
The real world is dynamic, yet most image fusion methods process static frames independently, ignoring temporal correlations in videos and leading to flickering and temporal incons…
Retinex-MEF: Retinex-based Glare Effects Aware Unsupervised Multi-Exposure Image Fusion
Haowen Bai, Jiangshe Zhang, Zixiang Zhao +3
Multi-exposure image fusion (MEF) synthesizes multiple, differently exposed images of the same scene into a single, well-exposed composite. Retinex theory, which separates image il…
Deep Unfolding Multi-modal Image Fusion Network via Attribution Analysis
Haowen Bai, Zixiang Zhao, Jiangshe Zhang +5
Multi-modal image fusion synthesizes information from multiple sources into a single image, facilitating downstream tasks such as semantic segmentation. Current approaches primaril…
Task-driven Image Fusion with Learnable Fusion Loss
Haowen Bai, Jiangshe Zhang, Zixiang Zhao +5
Multi-modal image fusion aggregates information from multiple sensor sources, achieving superior visual quality and perceptual features compared to single-source images, often impr…
Image Fusion via Vision-Language Model
Zixiang Zhao, Lilun Deng, Haowen Bai +8
Image fusion integrates essential information from multiple images into a single composite, enhancing structures, textures, and refining imperfections. Existing methods predominant…
ReFusion: Learning Image Fusion from Reconstruction with Learnable Loss via Meta-Learning
Haowen Bai, Zixiang Zhao, Jiangshe Zhang +5
Image fusion aims to combine information from multiple source images into a single one with more comprehensive informational content. Deep learning-based image fusion algorithms fa…