373 citations · 485 across the 23 of their papers we have counts for
24 papers
Advancing All-Weather Building Damage Mapping to the Instance Level: Outcomes and Insights from the 2026 Bright Challenge
Hongruixuan Chen, He Huang, Haifeng Wang +19
Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-event optical imagery, however, ma…
Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations
Junjue Wang, Weihao Xuan, Heli Qi +7
Operational disaster response goes beyond damage assessment, requiring responders to integrate multi-sensor signals, reason over road networks, populations and key facilities, plan…
GeoMMBench and GeoMMAgent: Toward Expert-Level Multimodal Intelligence in Geoscience and Remote Sensing
Aoran Xiao, Shihao Cheng, Yonghao Xu +3
Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and remote sensing (RS) remains con…
Smart Transfer: Leveraging Vision Foundation Model for Rapid Building Damage Mapping with Post-Earthquake VHR Imagery
Hao Li, Liwei Zou, Wenping Yin +4
Living in a changing climate, human society now faces more frequent and severe natural disasters than ever before. As a consequence, rapid disaster response during the "Golden 72 H…
MM-OVSeg:Multimodal Optical-SAR Fusion for Open-Vocabulary Segmentation in Remote Sensing
Yimin Wei, Aoran Xiao, Hongruixuan Chen +2
Open-vocabulary segmentation enables pixel-level recognition from an open set of textual categories, allowing generalization beyond fixed classes. Despite great potential in remote…
Enhancing Monocular Height Estimation via Sparse LiDAR-Guided Correction
Jian Song, Hongruixuan Chen, Naoto Yokoya
Monocular height estimation (MHE) from very-high-resolution (VHR) optical imagery remains challenging due to limited structural cues and the high cost and geographic constraints of…
SARLANG-1M: A Benchmark for Vision-Language Modeling in SAR Image Understanding
Yimin Wei, Aoran Xiao, Yexian Ren +4
Synthetic Aperture Radar (SAR) is a crucial remote sensing technology, enabling all-weather, day-and-night observation with strong surface penetration for precise and continuous en…
A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, Strategies, and Challenges
Lei Ding, Danfeng Hong, Maofan Zhao +6
In the last decade, the rapid development of deep learning (DL) has made it possible to perform automatic, accurate, and robust Change Detection (CD) on large volumes of Remote Sen…
OpenEarthMap-SAR: A Benchmark Synthetic Aperture Radar Dataset for Global High-Resolution Land Cover Mapping
Junshi Xia, Hongruixuan Chen, Clifford Broni-Bediako +3
High-resolution land cover mapping plays a crucial role in addressing a wide range of global challenges, including urban planning, environmental monitoring, disaster response, and…
BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response
Hongruixuan Chen, Jian Song, Olivier Dietrich +9
Disaster events occur around the world and cause significant damage to human life and property. Earth observation (EO) data enables rapid and comprehensive building damage assessme…
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic Segmentation
Ziyang Gong, Zhixiang Wei, Di Wang +13
The field of Remote Sensing Domain Generalization (RSDG) has emerged as a critical and valuable research frontier, focusing on developing models that generalize effectively across…
Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and Benchmark
Clifford Broni-Bediako, Junshi Xia, Jian Song +3
Learning with limited labelled data is a challenging problem in various applications, including remote sensing. Few-shot semantic segmentation is one approach that can encourage de…
GaussianOcc: Fully Self-supervised and Efficient 3D Occupancy Estimation with Gaussian Splatting
Wanshui Gan, Fang Liu, Hongbin Xu +2
We introduce GaussianOcc, a systematic method that investigates the two usages of Gaussian splatting for fully self-supervised and efficient 3D occupancy estimation in surround vie…
SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery
Jian Song, Hongruixuan Chen, Weihao Xuan +2
Global semantic 3D understanding from single-view high-resolution remote sensing (RS) imagery is crucial for Earth Observation (EO). However, this task faces significant challenges…
HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model
Di Wang, Meiqi Hu, Yao Jin +19
Accurate hyperspectral image (HSI) interpretation is critical for providing valuable insights into various earth observation-related applications such as urban planning, precision…
Unsupervised Domain Adaptation Architecture Search with Self-Training for Land Cover Mapping
Clifford Broni-Bediako, Junshi Xia, Naoto Yokoya
Unsupervised domain adaptation (UDA) is a challenging open problem in land cover mapping. Previous studies show encouraging progress in addressing cross-domain distribution shifts…
ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model
Hongruixuan Chen, Jian Song, Chengxi Han +2
Convolutional neural networks (CNN) and Transformers have made impressive progress in the field of remote sensing change detection (CD). However, both architectures have inherent s…
Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)
Hongruixuan Chen, Jian Song, Naoto Yokoya
Unsupervised multimodal change detection is pivotal for time-sensitive tasks and comprehensive multi-temporal Earth monitoring. In this study, we explore unsupervised multimodal ch…
Submeter-level Land Cover Mapping of Japan
Naoto Yokoya, Junshi Xia, Clifford Broni-Bediako
Deep learning has shown promising performance in submeter-level mapping tasks; however, the annotation cost of submeter-level imagery remains a challenge, especially when applied o…
Enhancing Monocular Height Estimation from Aerial Images with Street-view Images
Xiaomou Hou, Wanshui Gan, Naoto Yokoya
Accurate height estimation from monocular aerial imagery presents a significant challenge due to its inherently ill-posed nature. This limitation is rooted in the absence of adequa…
Flooding Regularization for Stable Training of Generative Adversarial Networks
Iu Yahiro, Takashi Ishida, Naoto Yokoya
Generative Adversarial Networks (GANs) have shown remarkable performance in image generation. However, GAN training suffers from the problem of instability. One of the main approac…
ObjFormer: Learning Land-Cover Changes From Paired OSM Data and Optical High-Resolution Imagery via Object-Guided Transformer
Hongruixuan Chen, Cuiling Lan, Jian Song +3
Optical high-resolution imagery and OSM data are two important data sources of change detection (CD). Previous related studies focus on utilizing the information in OSM data to aid…
Exchange means change: an unsupervised single-temporal change detection framework based on intra- and inter-image patch exchange
Hongruixuan Chen, Jian Song, Chen Wu +2
Change detection (CD) is a critical task in studying the dynamics of ecosystems and human activities using multi-temporal remote sensing images. While deep learning has shown promi…
SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection
Jian Song, Hongruixuan Chen, Naoto Yokoya
Synthetic datasets, recognized for their cost effectiveness, play a pivotal role in advancing computer vision tasks and techniques. However, when it comes to remote sensing image p…