4 citations · 14 across the 28 of their papers we have counts for
15 papers · 1 filter
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image
Shuang Xu, Zixiang Zhao, Haowen Bai +4
Hyperspectral images (HSIs) are frequently noisy and of low resolution due to the constraints of imaging devices. Recently launched satellites can concurrently acquire HSIs and pan…
Towards Satellite Image Road Graph Extraction: A Global-Scale Dataset and A Novel Method
Pan Yin, Kaiyu Li, Xiangyong Cao +5
Recently, road graph extraction has garnered increasing attention due to its crucial role in autonomous driving, navigation, etc. However, accurately and efficiently extracting roa…
Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction
Yuntao Shou, Peiqiang Yan, Xingjian Yuan +3
In recent years, histopathological whole slide image (WSI)- based survival analysis has attracted much attention in medical image analysis. In practice, WSIs usually come from diff…
SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images
Kaiyu Li, Ruixun Liu, Xiangyong Cao +4
Remote sensing image plays an irreplaceable role in fields such as agriculture, water resources, military, and disaster relief. Pixel-level interpretation is a critical aspect of r…
AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generation
Datao Tang, Xiangyong Cao, Xuan Wu +6
Remote sensing image object detection (RSIOD) aims to identify and locate specific objects within satellite or aerial imagery. However, there is a scarcity of labeled data in curre…
HSIGene: A Foundation Model For Hyperspectral Image Generation
Li Pang, Xiangyong Cao, Datao Tang +4
Hyperspectral image (HSI) plays a vital role in various fields such as agriculture and environmental monitoring. However, due to the expensive acquisition cost, the number of hyper…
SpeGCL: Self-supervised Graph Spectrum Contrastive Learning without Positive Samples
Yuntao Shou, Xiangyong Cao, Deyu Meng
Graph Contrastive Learning (GCL) excels at managing noise and fluctuations in input data, making it popular in various fields (e.g., social networks, and knowledge graphs). Our stu…
Chain-of-Restoration: Multi-Task Image Restoration Models are Zero-Shot Step-by-Step Universal Image Restorers
Jin Cao, Deyu Meng, Xiangyong Cao
Despite previous image restoration (IR) methods have often concentrated on isolated degradations, recent research has increasingly focused on addressing composite degradations invo…
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…
Open-CD: A Comprehensive Toolbox for Change Detection
Kaiyu Li, Jiawei Jiang, Andrea Codegoni +13
We present Open-CD, a change detection toolbox that contains a rich set of change detection methods as well as related components and modules. The toolbox started from a series of…
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…
SemiCD-VL: Visual-Language Model Guidance Makes Better Semi-supervised Change Detector
Kaiyu Li, Xiangyong Cao, Yupeng Deng +4
Change Detection (CD) aims to identify pixels with semantic changes between images. However, annotating massive numbers of pixel-level images is labor-intensive and costly, especia…
Rethinking the Graph Polynomial Filter via Positive and Negative Coupling Analysis
Haodong Wen, Bodong Du, Ruixun Liu +2
Recently, the optimization of polynomial filters within Spectral Graph Neural Networks (GNNs) has emerged as a prominent research focus. Existing spectral GNNs mainly emphasize pol…
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…