9 papers
Making Every Step Count: Spatio-Temporal Information Allocation for Imaging Inverse Problems
Yi Cao, Xiangyong Cao, Pei Liu +2
Flow-based generative models have emerged as powerful image priors for training-free inverse problem solving, capturing coherent semantics and fine-grained structure. Despite these…
HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation
Li Pang, Heng Zhao, Yijia Zhang +2
Hyperspectral image (HSI) restoration is crucial for reliable analysis, as real-world HSIs suffer from noise, blur, and resolution loss. However, existing models trained on source…
CGFformer: Cluster-Guidance Frequency Transformer for Pansharpening
Zijian Zhou, Jianing Zhang, Kai Sun +3
Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) images with high-resolution panchromatic (PAN) images. Howe…
The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
Kai Liu, Haoyang Yue, Zeli Lin +65
This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The challenge aims to recover high…
Motion-Enhanced Nonlocal Similarity Implicit Neural Representation for Infrared Dim and Small Target Detection
Pei Liu, Yisi Luo, Wenzhen Wang +1
Infrared dim and small target detection presents a significant challenge due to dynamic multi-frame scenarios and weak target signatures in the infrared modality. Traditional low-r…
Beyond Low-rankness: Guaranteed Matrix Recovery via Modified Nuclear Norm
Jiangjun Peng, Yisi Luo, Xiangyong Cao +2
The nuclear norm (NN) has been widely explored in matrix recovery problems, such as Robust PCA and matrix completion, leveraging the inherent global low-rank structure of the data.…