Remote Sensing VLMs

VLM: Vision-Language Model

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41 papers6 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Preserving the Manifold: Frozen Expert Alignment for Label-Efficient SAR Scene Understanding
Oct 18, 2026Eli A. Underwood, I. Taylor McKechnie, Leslie M. CollinsRemote Sensing VLMs Cross-Modal Alignment
Duke University
GeoReason: Bridging Logical Reasoning and Spatial Fidelity in Remote Sensing Segmentation
Oct 16, 2026Cheng Fan, Han Wu, Tingzhang Luo +3Reasoning Segmentation Remote Sensing Image Segmentation
City University of Hong Kong · School of Computer Science, Peking University · Samsung
FloodVLM-Pix: Language-Guided Pixel-Level Flood Understanding
Oct 16, 2026Chengyang Zhang, Zhihao Wang, Zhiyu Long +4Remote Sensing VLMs Text-Guided Image Segmentation
Tsinghua University · National Disaster Reduction Center
ReDiS: Reasoning-Diagnosis Self-Evolution for Multimodal Reasoning in Remote Sensing
Oct 13, 2026Yi Liu, Wentao Jiang, Shuo Ni +5Remote Sensing VLMs Multimodal Reasoning
School of Computer Science, Wuhan University · Zhongguancun Academy · National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing, Beijing Institute of Technology
GeoNLI - A Natural Language Interpreter for Satellite Imagery
Sep 23, 2026Ashutosh Gandhe, Anupam Rawat, Geet Sethi +5Remote Sensing Visual Grounding Remote Sensing VQA
Indian Institute of Technology, Bombay
The Earth in One Gaze: Training-Free Active Focus for UHR Remote Sensing Understanding
Sep 23, 2026Yao Zhang, Pengyu Dai, Wei Guo +5Remote Sensing Image Understanding Remote Sensing VLMs
Wuhan University
Exploring the Potential of Contrastive Language-Image Pre-training for Multi-Source Remote Sensing Data
Sep 3, 2026Xiangyang Miao, Kelu Yao, Yekai Huang +7Remote Sensing Image Understanding Remote Sensing VLMs
School of Computer Science and Technology, Zhejiang University · Space-based Computing System Research Center, Zhejiang Lab
AlignJEPA: Predictive Vision-Language Alignment for Remote Sensing Foundation Models
Aug 16, 2026Md Aminur Hossain, Omkumar Vaghasiya, Rajeev Ranjan Dwivedi +2Remote Sensing VLMs Vision-Language Alignment
Space Applications Centre, ISRO, Ahmedabad, India · Indian Institute of Science Education and Research (IISER) Bhopal, India · CSRE, Indian Institute of Technology Bombay, India
SA-GEM: Scale-Adaptive and Geospatial Evidence-Modulated Token Pruning for Efficient Remote Sensing Large Vision-Language Models
Aug 15, 2026Kexin Ma, Jing Xiao, Bowen Xing +2Remote Sensing VLMs Visual Token Pruning
School of Artificial Intelligence, Wuhan University · Hangzhou Institute of Technology, Xidian University · Department of Electrical Engineering, National Tsing Hua University
LongEarth-R1: Benchmarking and Aligning Vision-Language Models for Long-Horizon Earth Observation Reasoning
Aug 13, 2026Yupan Ding, Jing Xiao, Zhenyuan Zhang +4Remote Sensing Remote Sensing VQA
School of Artificial Intelligence, Wuhan University, Wuhan, China · School of Computer Science, Wuhan University, Wuhan, China · Xi’an University of Electronic Science and Technology, Xi’an, China +1
RSVideo: Are Your Vision-Language Models Ready for Remote Sensing Videos?
Aug 3, 2026Hongjie Zhou, Shiqin Wang, Haoyang Chen +5Video-Language Model Evaluation Remote Sensing
Wuhan University · Zhongguancun Academy
Beyond Zooming: Learning Multi-Tool Visual Reasoning for Ultra-High-Resolution Remote Sensing
Jul 28, 2026Fengxiang Wang, Jiangnan Huang, Mingshuo Chen +8RL for Tool Use Remote Sensing VQA
National University of Defense Technology · Wuhan University · Tsinghua University
Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion
Jul 28, 2026Junhyuk Heo, Junghwan ParkRemote Sensing Image Segmentation Few-Shot Semantic Segmentation
TelePIX, Seoul, Republic of Korea
Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?
Jul 22, 2026Qiwei Ma, Chunping Qiu, Xinjun Cheng +5Remote Sensing Image Understanding Remote Sensing VQA
School of Artificial Intelligence and Robotics, Hunan University, Changsha, 410082, China · Intelligent Game and Decision Lab (IGDL), Beijing, 100091, China · cYuelushan Center for Industrial Innovation, Changsha, 410082, China
More with Less: a Large Scale Remote Sensing VLM with a Simple Recipe
Jul 17, 2026Stefan Maria Ailuro, Mario Markov, Mohammad Mahdi +2Remote Sensing Image Understanding Remote Sensing VQA
INSAIT, Sofia University "St. Kliment Ohridski"
MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM Adaptation
Jul 7, 2026Jiaju Han, Ma Yaqi, Yahui Chai +8Remote Sensing Image Understanding VLM Adaptation
China University of Petroleum-Beijing at Karamay, Karamay, Xinjiang, China · Guizhou University, Guiyang, China · Shenzhen Research Institute of Big Data, Shenzhen, China +1
FusionRS: A Large-Scale RGB-Infrared Remote Sensing Dataset for Dual-Modal Vision-Language Foundation Models
Jun 15, 2026Jiaju Han, Ben Zhang, Xuemeng Sun +6Remote Sensing Image Understanding Remote Sensing Image Captioning
China University of Petroleum-Beijing at Karamay · University of Electronic Science and Technology of China · Tianjin University
Beyond Templates: Revisiting Zero-Shot Remote Sensing through Meta-Prompting
Jun 15, 2026Eirini Baltzi, Dionysis Christopoulos, Sotiris Spanos +2Remote Sensing Image Understanding Zero-Shot Image Classification
Remote Sensing Lab, National Technical University of Athens Athens, Greece · Department of Engineering and Sciences, Universitas Mercatorum Rome, Italy
Training-Free Open-Vocabulary Visual Grounding for Remote Sensing Images and Videos
Jun 15, 2026Ke Li, Di Wang, Yongshan Zhu +5Remote Sensing Image Understanding Temporal Video Grounding
School of Computer Science and Technology, Xidian University, Xi’an 710071, China · Interdisciplinary Institute of Artificial Intelligence, Xidian University, Xi’an, Shaanxi 710126, China · School of Artificial Intelligence, Xidian University, Xi’an 710071, China +2
Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks
Jun 9, 2026Miaoxin Cai, Guanqun Wang, Wei Zhang +6Multimodal Understanding Multimodal Grounding
National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing (SBIIP), Beijing Institute of Technology, Beijing 100081, China · Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing 100081, China · School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China +5
SkyNative: A Native Multimodal Framework for Remote Sensing Visual Evidence Reasoning
May 18, 2026Xiao Yang, Ronghao Fu, Zhiwen Lin +10VLM Evaluation VLM Robustness
College of Computer Science and Technology, Jilin University, China · Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education
GeoVista: Visually Grounded Active Perception for Vision-Language Understanding of Ultra-High-Resolution Remote Sensing Images
May 14, 2026Jiashun Zhu, Ronghao Fu, Jiasen Hu +3Remote Sensing Image Understanding Remote Sensing VQA
College of Computer Science and Technology, Jilin University, Changchun 130021, China · Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Changchun 130021, China · Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100000, China +1
SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models
May 11, 2026Chen Zhong, Xiao An, Jiaxing Sun +3VLM Evaluation Remote Sensing
Wuhan University · Shanghai Artificial Intelligent Laboratory
One Adapter, Every Resolution: Gated Low-Rank Adaptation for Remote Sensing VLMs
May 8, 2026Song Zhang, Yanlong Chen, Yining Chen +2Remote Sensing Image Understanding Remote Sensing VQA
Nanjing University · ETH Zurich · Nanjing University of Posts and Telecommunications
ChangeQuery: Advancing Remote Sensing Change Analysis for Natural and Human-Induced Disasters from Visual Detection to Semantic Understanding
Apr 24, 2026Dongwei Sun, Jing Yao, Kan Wei +6Remote Sensing Image Understanding Disaster Damage Assessment
School of Computer Science and Technology and the Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an 710049, China · State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China +4
Revisiting Change VQA in Remote Sensing with Structured and Native Multimodal Qwen Models
Apr 20, 2026Yakoub Bazi, Mohamad M. Al Rahhal, Mansour Zuair +1VLM Evaluation Remote Sensing Image Understanding
Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia · Applied Computer Science Department, College of Applied Computer Science, King Saud University, Riyadh 11543, Saudi Arabia
RS-HyRe-R1: A Hybrid Reward Mechanism to Overcome Perceptual Inertia for Remote Sensing Images Understanding
Apr 19, 2026Gaozhi Zhou, Hu He, Peng Shen +8Vision-Language Models Visual Question Answering
School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China · School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift
Apr 10, 2026Harshith Kethavath, Weiming HuVLM Adaptation Remote Sensing VLMs
University of Georgia, USA
ProVG: Progressive Visual Grounding via Language Decoupling for Remote Sensing Imagery
Apr 2, 2026Ke Li, Ting Wang, Di Wang +4Remote Sensing Visual Grounding Remote Sensing VLMs
Xidian University, China · UC San Diego, USA · SUST, China
Continual Vision-Language Learning for Remote Sensing: Benchmarking and Analysis
Apr 1, 2026Xingxing Weng, Ruifeng Ni, Chao Pang +5Remote Sensing VLMs Continual Learning for VLMs
School of Computer Science, Wuhan University · College of Resources and Environmental Sciences, Shanxi Agricultural University · School of Artificial Intelligence, Wuhan University +2

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Preserving the Manifold: Frozen Expert Alignment for Label-Efficient SAR Scene Understanding

Eli A. Underwood, I. Taylor McKechnie, Leslie M. Collins

Duke University

Remote Sensing VLMs Cross-Modal Alignment Data-Efficient Learning Multimodal Contrastive Learning Remote Sensing Scene Classification

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Cross-modal alignment of synthetic aperture radar (SAR) imagery to natural language is constrained by two distinct failures. The first is modality mismatch: text encoders pre-trained on optical imagery, such as CLIP, cannot be efficiently fine-tuned on SAR, because active microwave backscatter is physically incompatible with passive optical reflectance and the available SAR caption datasets are orders of magnitude too small to bridge this gap without substantially degrading the learned semantic manifold. The second is physical forgetting: SAR encoders pre-trained on large-scale self-supervised objectives encode radar physics that are progressively erased when the encoder is fine-tuned for text alignment on limited caption data. A single design principle addresses both failures: keep both encoders frozen and learn only a constrained, structure-preserving bridge. Our Frozen Expert framework aligns a frozen CROMA SAR encoder with a frozen CLIP text encoder via a lightweight constrained residual bridge. We formally define physical forgetting via Procrustes disparity and show our bridge preserves SAR geometry significantly better than fine-tuning (disparity: 0.210 vs. 0.351). We validate generality across multiple SAR backbones and text encoders. On zero-shot SAR scene classification, our approach outperforms fine-tuned baselines using up to 8x less training data: DFC2020 (+10.3% R@1, +15.5% mAP), EuroSAT-SAR (+15.7% R@1, +12.2% mAP), BigEarthNet-MM (+14.7% R@1). These results establish frozen manifold alignment as a principled, data-efficient alternative to fine-tuning in high-disparity cross-modal settings.