559 citations · 887 across the 34 of their papers we have counts for
35 papers · 1 filter
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…
SFR-Net: Learning Scale-Frustum Representations for Ultra-Wide Area Remote Sensing Image Segmentation
Chuyu Zhong, Keyan Chen, Qinzhe Yang +3
Pixel count and geographical coverage are two key characteristics of remote sensing images. Existing remote sensing image segmentation methods typically focus on images with either…
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…
Multi-Modal Building Change Detection for Large-Scale Small Changes: Benchmark and Baseline
Ye Wang, Wei Lu, Zhihui You +6
Change detection in optical remote sensing imagery is susceptible to illumination fluctuations, seasonal changes, and variations in surface land-cover materials. Relying solely on…
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…
AgriFM: A Multi-source Temporal Remote Sensing Foundation Model for Agriculture Mapping
Wenyuan Li, Shunlin Liang, Keyan Chen +7
Accurate crop mapping fundamentally relies on modeling multi-scale spatiotemporal patterns, where spatial scales range from individual field textures to landscape-level context, an…
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…
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…
Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model
Chenyang Liu, Keyan Chen, Rui Zhao +2
Generative foundation models have advanced large-scale text-driven natural image generation, becoming a prominent research trend across various vertical domains. However, in the re…
Remote Sensing SpatioTemporal Vision-Language Models: A Comprehensive Survey
Chenyang Liu, Jiafan Zhang, Keyan Chen +3
The interpretation of multi-temporal remote sensing imagery is critical for monitoring Earth's dynamic processes-yet previous change detection methods, which produce binary or sema…
Semantic-CC: Boosting Remote Sensing Image Change Captioning via Foundational Knowledge and Semantic Guidance
Yongshuo Zhu, Lu Li, Keyan Chen +3
Remote sensing image change captioning (RSICC) aims to articulate the changes in objects of interest within bi-temporal remote sensing images using natural language. Given the limi…
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…
CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection
Haotian Zhang, Keyan Chen, Chenyang Liu +3
Recently, the Mamba architecture based on state space models has demonstrated remarkable performance in a series of natural language processing tasks and has been rapidly applied t…
RSCaMa: Remote Sensing Image Change Captioning with State Space Model
Chenyang Liu, Keyan Chen, Bowen Chen +3
Remote Sensing Image Change Captioning (RSICC) aims to describe surface changes between multi-temporal remote sensing images in language, including the changed object categories, l…
MarsSeg: Mars Surface Semantic Segmentation with Multi-level Extractor and Connector
Junbo Li, Keyan Chen, Gengju Tian +2
The segmentation and interpretation of the Martian surface play a pivotal role in Mars exploration, providing essential data for the trajectory planning and obstacle avoidance of r…
RSMamba: Remote Sensing Image Classification with State Space Model
Keyan Chen, Bowen Chen, Chenyang Liu +3
Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation. The recent advancements…
Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
Chenyang Liu, Keyan Chen, Haotian Zhang +3
Monitoring changes in the Earth's surface is crucial for understanding natural processes and human impacts, necessitating precise and comprehensive interpretation methodologies. Re…
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
Zili Liu, Hao Chen, Lei Bai +6
Downscaling (DS) of meteorological variables involves obtaining high-resolution states from low-resolution meteorological fields and is an important task in weather forecasting. Pr…
Learning to detect cloud and snow in remote sensing images from noisy labels
Zili Liu, Hao Chen, Wenyuan Li +5
Detecting clouds and snow in remote sensing images is an essential preprocessing task for remote sensing imagery. Previous works draw inspiration from semantic segmentation models…