559 citations · 887 across the 34 of their papers we have counts for
38 papers
ReTAC: Residual Test-Time Agentic Computation for Video Spatial Reasoning
Yike Wu, Keyan Chen, Qixiong Wang +6
Test-time agentic computation can improve multimodal large language models (MLLMs) through planning, tool use, iterative perception, and reflection, but indiscriminate computation…
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…
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…
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…