71 citations · 432 across the 57 of their papers we have counts for
60 papers
Remote Sensing Sparse-View 3D Gaussian Splatting via Depth Image-Based Rendering
Jiaming Kang, Zhengxia Zou, Zhenwei Shi
Remote sensing novel view synthesis under sparse observations remains challenging due to insufficient geometric constraints and limited cross-view supervision. Existing Neural Radi…
UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations
Songru Yang, Zili Liu, Tao Han +7
Global In-situ Observation (GIO) provides fine-scale, direct records of the global weather system from sparse point stations, making it an indispensable source for capturing locali…
LoRetta: A Foundation Model and Extensive Dataset for Global-Scale Remote Sensing Dense Image Matching
Siwei Yu, Han Guo, Zhenwei Shi +1
Dense image matching establishes pixel-wise correspondences and underpins broad applications in computer vision and photogrammetry. However, extending dense matching to global-scal…
FootprintNet: State-Transition-Guided Dynamic Footprint Learning for Multi-temporal Remote Sensing Change Detection
Haotian Zhang, Hao Chen, Han Guo +2
Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at each spatial location over…
TSSM: Triaxial State Space Model for Global Station Weather Forecasting with Temporal-Variable-Historical Modeling
Songru Yang, Zili Liu, Tao Han +7
Global Station Weather Forecasting (GSWF) is pivotal for localized and extreme weather prediction over key regions. Despite efforts to exploit look-back windows, existing methods s…
LEVIRDet: A Million-Scale 159-Category Dataset and Foundation Model for Universal Remote Sensing Object Detection
Qinzhe Yang, Dongyu Wang, Haohan Niu +3
Remote sensing object detection has advanced rapidly with the development of large-scale benchmarks and modern detection architectures. However, existing datasets and detectors rem…
State Space Models Meet Remote Sensing: A Survey
Qinzhe Yang, Chenyang Liu, Jia Xu +2
State Space Models (SSMs), designed for long-range modeling, offer linear computational complexity and strong capabilities in capturing long-range dependencies. In the field of rem…
Efficient Remote Sensing Instance Segmentation with Linear-Time State Space Distilled Visual Foundation Models
Qinzhe Yang, Keyan Chen, Jia Xu +2
The computational complexity of Transformers scales quadratically with the number of tokens, which significantly constrains the efficiency of vision models, particularly recent ViT…
MetaEarth-MM: Unified Multimodal Remote Sensing Image Generation with Scene-centered Joint Modeling
Zhiping Yu, Chenyang Liu, Jinqi Cao +4
Multi-modal remote sensing images are vital for Earth observation, yet complete paired observations are often scarce in practice. Existing generative methods commonly address this…
CloudMamba: An Uncertainty-Guided Dual-Scale Mamba Network for Cloud Detection in Remote Sensing Imagery
Jiajun Yang, Keyan Chen, Zhengxia Zou +1
Cloud detection in remote sensing imagery is a fundamental, critical, and highly challenging problem. Existing deep learning-based cloud detection methods generally formulate it as…
Think and Answer ME: Benchmarking and Exploring Multi-Entity Reasoning Grounding in Remote Sensing
Shuchang Lyu, Haiquan Wen, Guangliang Cheng +5
Recent advances in reasoning language models and reinforcement learning with verifiable rewards have significantly enhanced multi-step reasoning capabilities. This progress motivat…
TaCo: Capturing Spatio-Temporal Semantic Consistency in Remote Sensing Change Detection
Han Guo, Chenyang Liu, Haotian Zhang +3
Remote sensing change detection (RSCD) aims to identify surface changes across bi-temporal satellite images. Most previous methods rely solely on mask supervision, which effectivel…
FoBa: A Foreground-Background co-Guided Method and New Benchmark for Remote Sensing Semantic Change Detection
Haotian Zhang, Han Guo, Keyan Chen +3
Despite the remarkable progress achieved in remote sensing semantic change detection (SCD), two major challenges remain. At the data level, existing SCD datasets suffer from limite…
RSRefSeg 2: Decoupling Referring Remote Sensing Image Segmentation with Foundation Models
Keyan Chen, Chenyang Liu, Bowen Chen +3
Referring Remote Sensing Image Segmentation provides a flexible and fine-grained framework for remote sensing scene analysis via vision-language collaborative interpretation. Curre…
Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method
Wenyuan Li, Shunlin Liang, Yuxiang Zhang +8
Fine-grained crop type classification serves as the fundamental basis for large-scale crop mapping and plays a vital role in ensuring food security. It requires simultaneous captur…
SeG-SR: Integrating Semantic Knowledge into Remote Sensing Image Super-Resolution via Vision-Language Model
Bowen Chen, Keyan Chen, Mohan Yang +2
High-resolution (HR) remote sensing imagery plays a vital role in a wide range of applications, including urban planning and environmental monitoring. However, due to limitations i…
BlockGaussian: Efficient Large-Scale Scene Novel View Synthesis via Adaptive Block-Based Gaussian Splatting
Yongchang Wu, Zipeng Qi, Zhenwei Shi +1
The recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated remarkable potential in novel view synthesis tasks. The divide-and-conquer paradigm has enabled large-scal…
Heterogeneous Mixture of Experts for Remote Sensing Image Super-Resolution
Bowen Chen, Keyan Chen, Mohan Yang +2
Remote sensing image super-resolution (SR) aims to reconstruct high-resolution remote sensing images from low-resolution inputs, thereby addressing limitations imposed by sensors a…
DynamicVis: Dynamic Visual Perception for Efficient Remote Sensing Foundation Models
Keyan Chen, Chenyang Liu, Bowen Chen +4
The advancement of RS technology has enabled high-resolution Earth observation; however, interpreting these images using modern VFMs remains a significant challenge. Unlike object-…
TriDF: Triplane-Accelerated Density Fields for Few-Shot Remote Sensing Novel View Synthesis
Jiaming Kang, Keyan Chen, Zhengxia Zou +1
Remote sensing novel view synthesis (NVS) offers significant potential for 3D interpretation of remote sensing scenes, with important applications in urban planning and environment…
Kolmogorov Arnold Neural Interpolator for Downscaling and Correcting Meteorological Fields from In-Situ Observations
Zili Liu, Hao Chen, Lei Bai +3
Obtaining accurate weather forecasts at station locations is a critical challenge due to systematic biases arising from the mismatch between multi-scale, continuous atmospheric cha…
WSSM: Geographic-enhanced hierarchical state-space model for global station weather forecast
Songru Yang, Zili Liu, Zhenwei Shi +1
Global Station Weather Forecasting (GSWF), a prominent meteorological research area, is pivotal in providing timely localized weather predictions. Despite the progress existing mod…
RSRefSeg: Referring Remote Sensing Image Segmentation with Foundation Models
Keyan Chen, Jiafan Zhang, Chenyang Liu +2
Referring remote sensing image segmentation is crucial for achieving fine-grained visual understanding through free-format textual input, enabling enhanced scene and object extract…
Semantic-CD: Remote Sensing Image Semantic Change Detection towards Open-vocabulary Setting
Yongshuo Zhu, Lu Li, Keyan Chen +3
Remote sensing image semantic change detection is a method used to analyze remote sensing images, aiming to identify areas of change as well as categorize these changes within imag…