4 citations · 14 across the 28 of their papers we have counts for
31 papers
HyperSAM: A Promptable Foundation Model for Hyperspectral Remote Sensing
Li Pang, Xinqiao Wu, Jing Yao +5
Hyperspectral remote sensing provides dense spectral measurements that are indispensable for material-level Earth observation, yet the construction of a general-purpose hyperspectr…
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…
Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration
Feiyu Tan, Qi Xie, Zongben Xu +1
Image restoration is an inherently ill posed inverse problem. Equivariant networks that embed geometric symmetry priors can mitigate this ill posedness and improve performance. How…
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…
Layout-Guided Controllable Pathology Image Generation with In-Context Diffusion Transformers
Yuntao Shou, Xiangyong Cao, Qian Zhao +1
Controllable pathology image synthesis requires reliable regulation of spatial layout, tissue morphology, and semantic detail. However, existing text-guided diffusion models offer…
Neural Approximation and Its Applications
Wei-Hao Wu, Ting-Zhu Huang, Xi-Le Zhao +2
Multivariate function approximation is a fundamental problem in machine learning. Classic multivariate function approximations rely on hand-crafted basis functions (e.g., polynomia…
SegEarth-R2: Towards Comprehensive Language-guided Segmentation for Remote Sensing Images
Zepeng Xin, Kaiyu Li, Luodi Chen +6
Effectively grounding complex language to pixels in remote sensing (RS) images is a critical challenge for applications like disaster response and environmental monitoring. Current…
SegEarth-OV3: Exploring SAM 3 for Open-Vocabulary Semantic Segmentation in Remote Sensing Images
Kaiyu Li, Shengqi Zhang, Yujie Wang +4
Most existing methods for training-free open-vocabulary semantic segmentation are based on CLIP. While these approaches have made progress, they often face challenges in precise lo…
Designing Domain-Specific Agents via Hierarchical Task Abstraction Mechanism
Kaiyu Li, Jiayu Wang, Zhi Wang +4
LLM-driven agents, particularly those using general frameworks like ReAct or human-inspired role-playing, often struggle in specialized domains that necessitate rigorously structur…
ZoomEarth: Active Perception for Ultra-High-Resolution Geospatial Vision-Language Tasks
Ruixun Liu, Bowen Fu, Jiayi Song +7
Ultra-high-resolution (UHR) remote sensing (RS) images offer rich fine-grained information but also present challenges in effective processing. Existing dynamic resolution and toke…
DescribeEarth: Describe Anything for Remote Sensing Images
Kaiyu Li, Zixuan Jiang, Xiangyong Cao +4
Automated textual description of remote sensing images is crucial for unlocking their full potential in diverse applications, from environmental monitoring to urban planning and di…
Annotation-Free Open-Vocabulary Segmentation for Remote-Sensing Images
Kaiyu Li, Xiangyong Cao, Ruixun Liu +4
Semantic segmentation of remote sensing (RS) images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high exp…
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.…
RS-MTDF: Multi-Teacher Distillation and Fusion for Remote Sensing Semi-Supervised Semantic Segmentation
Jiayi Song, Kaiyu Li, Xiangyong Cao +1
Semantic segmentation in remote sensing images is crucial for various applications, yet its performance is heavily reliant on large-scale, high-quality pixel-wise annotations, whic…
SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model
Kaiyu Li, Zepeng Xin, Li Pang +7
Remote sensing has become critical for understanding environmental dynamics, urban planning, and disaster management. However, traditional remote sensing workflows often rely on ex…
DynamicEarth: How Far are We from Open-Vocabulary Change Detection?
Kaiyu Li, Xiangyong Cao, Yupeng Deng +4
Monitoring Earth's evolving land covers requires methods capable of detecting changes across a wide range of categories and contexts. Existing change detection methods are hindered…
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…