305 citations · 652 across the 23 of their papers we have counts for
23 papers
HAIR: Hypernetworks-based All-in-One Image Restoration
Jin Cao, Yi Cao, Li Pang +2
Image restoration aims to recover a high-quality clean image from its degraded version. Recent progress in image restoration has demonstrated the effectiveness of All-in-One image…
Variational Zero-shot Multispectral Pansharpening
Xiangyu Rui, Xiangyong Cao, Yining Li +1
Pansharpening aims to generate a high spatial resolution multispectral image (HRMS) by fusing a low spatial resolution multispectral image (LRMS) and a panchromatic image (PAN). Th…
CRS-Diff: Controllable Remote Sensing Image Generation with Diffusion Model
Datao Tang, Xiangyong Cao, Xingsong Hou +3
The emergence of generative models has revolutionized the field of remote sensing (RS) image generation. Despite generating high-quality images, existing methods are limited in rel…
HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models
Li Pang, Xiangyu Rui, Long Cui +3
Hyperspectral image (HSI) restoration aims at recovering clean images from degraded observations and plays a vital role in downstream tasks. Existing model-based methods have limit…
A New Learning Paradigm for Foundation Model-based Remote Sensing Change Detection
Kaiyu Li, Xiangyong Cao, Deyu Meng
Change detection (CD) is a critical task to observe and analyze dynamic processes of land cover. Although numerous deep learning-based CD models have performed excellently, their f…
Neural Gradient Regularizer
Shuang Xu, Yifan Wang, Zixiang Zhao +6
Owing to its significant success, the prior imposed on gradient maps has consistently been a subject of great interest in the field of image processing. Total variation (TV), one o…
Masked Contrastive Graph Representation Learning for Age Estimation
Yuntao Shou, Xiangyong Cao, Deyu Meng
Age estimation of face images is a crucial task with various practical applications in areas such as video surveillance and Internet access control. While deep learning-based age e…
A Low-rank Matching Attention based Cross-modal Feature Fusion Method for Conversational Emotion Recognition
Yuntao Shou, Huan Liu, Xiangyong Cao +2
Conversational emotion recognition (CER) is an important research topic in human-computer interactions. {Although recent advancements in transformer-based cross-modal fusion method…
HIDFlowNet: A Flow-Based Deep Network for Hyperspectral Image Denoising
Qizhou Wang, Li Pang, Xiangyong Cao +2
Hyperspectral image (HSI) denoising is essentially ill-posed since a noisy HSI can be degraded from multiple clean HSIs. However, existing deep learning (DL)-based approaches only…
PanFlowNet: A Flow-Based Deep Network for Pan-sharpening
Gang Yang, Xiangyong Cao, Wenzhe Xiao +4
Pan-sharpening aims to generate a high-resolution multispectral (HRMS) image by integrating the spectral information of a low-resolution multispectral (LRMS) image with the texture…
Unsupervised Hyperspectral Pansharpening via Low-rank Diffusion Model
Xiangyu Rui, Xiangyong Cao, Li Pang +3
Hyperspectral pansharpening is a process of merging a high-resolution panchromatic (PAN) image and a low-resolution hyperspectral (LRHS) image to create a single high-resolution hy…
Probability-based Global Cross-modal Upsampling for Pansharpening
Zeyu Zhu, Xiangyong Cao, Man Zhou +2
Pansharpening is an essential preprocessing step for remote sensing image processing. Although deep learning (DL) approaches performed well on this task, current upsampling methods…
A Data-driven Loss Weighting Scheme across Heterogeneous Tasks for Image Denoising
Xiangyu Rui, Xiangyong Cao, Xile Zhao +2
In a variational denoising model, weight in the data fidelity term plays the role of enhancing the noise-removal capability. It is profoundly correlated with noise information, whi…
Fast Noise Removal in Hyperspectral Images via Representative Coefficient Total Variation
Jiangjun Peng, Hailin Wang, Xiangyong Cao +3
Mining structural priors in data is a widely recognized technique for hyperspectral image (HSI) denoising tasks, whose typical ways include model-based methods and data-based metho…
Memory-augmented Deep Unfolding Network for Guided Image Super-resolution
Man Zhou, Keyu Yan, Jinshan Pan +3
Guided image super-resolution (GISR) aims to obtain a high-resolution (HR) target image by enhancing the spatial resolution of a low-resolution (LR) target image under the guidance…
Proximal PanNet: A Model-Based Deep Network for Pansharpening
Xiangyong Cao, Yang Chen, Wenfei Cao
Recently, deep learning techniques have been extensively studied for pansharpening, which aims to generate a high resolution multispectral (HRMS) image by fusing a low resolution m…
Polarimetric SAR Image Semantic Segmentation with 3D Discrete Wavelet Transform and Markov Random Field
Haixia Bi, Lin Xu, Xiangyong Cao +2
Polarimetric synthetic aperture radar (PolSAR) image segmentation is currently of great importance in image processing for remote sensing applications. However, it is a challenging…
New Interpretations of Normalization Methods in Deep Learning
Jiacheng Sun, Xiangyong Cao, Hanwen Liang +3
In recent years, a variety of normalization methods have been proposed to help train neural networks, such as batch normalization (BN), layer normalization (LN), weight normalizati…
Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding
Minghan Li, Xiangyong Cao, Qian Zhao +3
Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely degenerate the performance of…
Discovering Influential Factors in Variational Autoencoders
Shiqi Liu, Jingxin Liu, Qian Zhao +5
In the field of machine learning, it is still a critical issue to identify and supervise the learned representation without manually intervening or intuition assistance to extract…
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network
Xiangyong Cao, Feng Zhou, Lin Xu +3
This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian…
Denoising Hyperspectral Image with Non-i.i.d. Noise Structure
Yang Chen, Xiangyong Cao, Qian Zhao +2
Hyperspectral image (HSI) denoising has been attracting much research attention in remote sensing area due to its importance in improving the HSI qualities. The existing HSI denois…
Low-rank Matrix Factorization under General Mixture Noise Distributions
Xiangyong Cao, Qian Zhao, Deyu Meng +2
Many computer vision problems can be posed as learning a low-dimensional subspace from high dimensional data. The low rank matrix factorization (LRMF) represents a commonly utilize…