papers

Publications (42)

cs.CV2026

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…

physics.ao-ph2024

DeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for Accurate and Continuous Weather Modeling

Wenyuan Li, Zili Liu, Keyan Chen +4

Accurate weather forecasting holds significant importance to human activities. Currently, there are two paradigms for weather forecasting: Numerical Weather Prediction (NWP) and De…

cs.CV2023

Continuous Cross-resolution Remote Sensing Image Change Detection

Hao Chen, Haotian Zhang, Keyan Chen +4

Most contemporary supervised Remote Sensing (RS) image Change Detection (CD) approaches are customized for equal-resolution bitemporal images. Real-world applications raise the nee…

cs.CV2024

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…

cs.CV2026

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-…

eess.IV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

Zero-Shot Image Harmonization with Generative Model Prior

Jianqi Chen, Yilan Zhang, Zhengxia Zou +2

We propose a zero-shot approach to image harmonization, aiming to overcome the reliance on large amounts of synthetic composite images in existing methods. These methods, while sho…

cs.CV2023

RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model

Keyan Chen, Chenyang Liu, Hao Chen +4

Leveraging the extensive training data from SA-1B, the Segment Anything Model (SAM) demonstrates remarkable generalization and zero-shot capabilities. However, as a category-agnost…

cs.CV2023

Continuous Remote Sensing Image Super-Resolution based on Context Interaction in Implicit Function Space

Keyan Chen, Wenyuan Li, Sen Lei +4

Despite its fruitful applications in remote sensing, image super-resolution is troublesome to train and deploy as it handles different resolution magnifications with separate model…

cs.CV2024

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…

cs.CV2023

Dense Pixel-to-Pixel Harmonization via Continuous Image Representation

Jianqi Chen, Yilan Zhang, Zhengxia Zou +2

High-resolution (HR) image harmonization is of great significance in real-world applications such as image synthesis and image editing. However, due to the high memory costs, exist…

cs.CV2021

Geographical Knowledge-driven Representation Learning for Remote Sensing Images

Wenyuan Li, Keyan Chen, Hao Chen +1

The proliferation of remote sensing satellites has resulted in a massive amount of remote sensing images. However, due to human and material resource constraints, the vast majority…

cs.CV2024

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…

cs.CV2024

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…

eess.IV2024

Reconstruction of Cardiac Cine MRI Using Motion-Guided Deformable Alignment and Multi-Resolution Fusion

Xiaoxiang Han, Yang Chen, Qiaohong Liu +4

Cardiac cine magnetic resonance imaging (MRI) is one of the important means to assess cardiac functions and vascular abnormalities. Mitigating artifacts arising during image recons…

cs.LG2026

Deep Gaussian Processes for Functional Maps

Matthew Lowery, Zhitong Xu, Da Long +5

Learning mappings between functional spaces, also known as function-on-function regression, is a fundamental problem in functional data analysis with broad applications, including…

cs.LG2026

Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data

Keyan Chen, Yile Li, Da Long +4

Neural operators have shown great potential in surrogate modeling. However, training a well-performing neural operator typically requires a substantial amount of data, which can po…

cs.CV2023

OvarNet: Towards Open-vocabulary Object Attribute Recognition

Keyan Chen, Xiaolong Jiang, Yao Hu +4

In this paper, we consider the problem of simultaneously detecting objects and inferring their visual attributes in an image, even for those with no manual annotations provided at…

cs.CV2025

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…

cs.CV2026

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…

eess.IV2025

MambaEviScrib: Mamba and Evidence-Guided Consistency Enhance CNN Robustness for Scribble-Based Weakly Supervised Ultrasound Image Segmentation

Xiaoxiang Han, Xinyu Li, Jiang Shang +5

Segmenting anatomical structures and lesions from ultrasound images contributes to disease assessment. Weakly supervised learning (WSL) based on sparse annotation has achieved enco…

cs.CV2026

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…

cs.CV2023

Diffusion Models for Imperceptible and Transferable Adversarial Attack

Jianqi Chen, Hao Chen, Keyan Chen +3

Many existing adversarial attacks generate -norm perturbations on image RGB space. Despite some achievements in transferability and attack success rate, the crafted adversaria…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

Pixel-Level Change Detection Pseudo-Label Learning for Remote Sensing Change Captioning

Chenyang Liu, Keyan Chen, Zipeng Qi +3

The existing methods for Remote Sensing Image Change Captioning (RSICC) perform well in simple scenes but exhibit poorer performance in complex scenes. This limitation is primarily…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2023

Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection

Keyan Chen, Chengyang Liu, Wenyuan Li +5

Change detection, a prominent research area in remote sensing, is pivotal in observing and analyzing surface transformations. Despite significant advancements achieved through deep…

cs.CV2023

Object Detection in 20 Years: A Survey

Zhengxia Zou, Keyan Chen, Zhenwei Shi +2

Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Over the past two decades, we have seen…

cs.LG2026

Arbitrarily Conditioned Hierarchical Flows for Spatiotemporal Events

Keyan Chen, Qiwei Yuan, Zhitong Xu +2

Events in spatiotemporal systems are ubiquitous, yet modeling their complex distributions remains challenging. Existing point process models often rely on strong structural assumpt…