3 citations · 4 across the 5 of their papers we have counts for
5 papers
Self-supervised Multiplex Consensus Mamba for General Image Fusion
Yingying Wang, Rongjin Zhuang, Hui Zheng +4
Image fusion integrates complementary information from different modalities to generate high-quality fused images, thereby enhancing downstream tasks such as object detection and s…
MMMamba: A Versatile Cross-Modal In Context Fusion Framework for Pan-Sharpening and Zero-Shot Image Enhancement
Yingying Wang, Xuanhua He, Chen Wu +5
Pan-sharpening aims to generate high-resolution multispectral (HRMS) images by integrating a high-resolution panchromatic (PAN) image with its corresponding low-resolution multispe…
Training-Free Large Model Priors for Multiple-in-One Image Restoration
Xuanhua He, Lang Li, Yingying Wang +7
Image restoration aims to reconstruct the latent clear images from their degraded versions. Despite the notable achievement, existing methods predominantly focus on handling specif…
AMSA-UNet: An Asymmetric Multiple Scales U-net Based on Self-attention for Deblurring
Yingying Wang
The traditional ingle-scale U-Net often leads to the loss of spatial information during deblurring, which affects the deblurring accracy. Additionally, due to the convolutional met…
Pan-Mamba: Effective pan-sharpening with State Space Model
Xuanhua He, Ke Cao, Keyu Yan +4
Pan-sharpening involves integrating information from low-resolution multi-spectral and high-resolution panchromatic images to generate high-resolution multi-spectral counterparts.…