mlsanityData to 14 Oct 2026

Vision-Language Models in Remote Sensing: Current Progress and Future Trends

arXiv 2305.05726 ↗First posted 9 May 2023cs.CV cs.AIcited by 93

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

Abstract (arXiv)

The remarkable achievements of ChatGPT and GPT-4 have sparked a wave of interest and research in the field of large language models for Artificial General Intelligence (AGI). These models provide intelligent solutions close to human thinking, enabling us to use general artificial intelligence to solve problems in various applications. However, in remote sensing (RS), the scientific literature on the implementation of AGI remains relatively scant. Existing AI-related research in remote sensing primarily focuses on visual understanding tasks while neglecting the semantic understanding of the objects and their relationships. This is where vision-language models excel, as they enable reasoning about images and their associated textual descriptions, allowing for a deeper understanding of the underlying semantics. Vision-language models can go beyond visual recognition of RS images, model semantic relationships, and generate natural language descriptions of the image. This makes them better suited for tasks requiring visual and textual understanding, such as image captioning, and visual question answering. This paper provides a comprehensive review of the research on vision-language models in remote sensing, summarizing the latest progress, highlighting challenges, and identifying potential research opportunities.

Key facts. Cited by 93 papers in the map (data through 14 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 170 of its 292 references that are in the map. First posted on arXiv 9 May 2023.

Builds on

170 of 292 references.

References · 170

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  4. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  5. 2020Language Models are Few-Shot Learnerscited by 32,419
  6. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  7. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  8. 2023GPT-4 Technical Reportcited by 18,396
  9. 2022Training language models to follow instructions with human feedbackcited by 15,971
  10. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  11. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  12. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
38 more
  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  6. 2023Segment Anythingcited by 8,234
  7. 2023Visual Instruction Tuningcited by 7,869
  8. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  9. 2020End-to-End Object Detection with Transformerscited by 7,414
  10. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,403
  11. 2016Densely Connected Convolutional Networkscited by 6,720
  12. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  13. 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Modelscited by 6,137
  14. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
  15. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  16. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,795
  17. 2017Neural Discrete Representation Learningcited by 4,712
  18. 2020Training data-efficient image transformers & distillation through attentioncited by 4,586
  19. 2022Flamingo: a Visual Language Model for Few-Shot Learningcited by 4,386
  20. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  21. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,322
  22. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  23. 2014Going Deeper with Convolutionscited by 4,241
  24. 2019Parameter-Efficient Transfer Learning for NLPcited by 4,236
  25. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,152
  26. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  27. 2021Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervisioncited by 3,864
  28. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  29. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  30. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
  31. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  32. 2016Improved Techniques for Training GANscited by 2,970
  33. 2015Fast R-CNNcited by 2,933
  34. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
  35. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
  36. 2023MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Modelscited by 2,711
  37. 2018YOLOv3: An Incremental Improvementcited by 2,659
  38. 2016Aggregated Residual Transformations for Deep Neural Networkscited by 2,546

50 most cited of 170 All 170 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 10; 2024: 20; 2025: 43; 2026: 20.

93 papers.

Sort:

By area:

  1. 2023RSGPT: A Remote Sensing Vision Language Model and Benchmarkcited by 207
  2. 2023RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensingcited by 151
  3. 2024LHRS-Bot: Empowering Remote Sensing with VGI-Enhanced Large Multimodal Language Modelcited by 138
  4. 2024VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understandingcited by 121
  5. 2023Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignmentcited by 71
  6. 2024TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Datacited by 70
  7. 2025Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Modelcited by 48
  8. 2024Towards Vision-Language Geo-Foundation Model: A Surveycited by 36
  9. 2024Large Language Models for Captioning and Retrieving Remote Sensing Imagescited by 30
  10. 2025Vision-Language Models for Edge Networks: A Comprehensive Surveycited by 29
  11. 2023Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forwardcited by 28
  12. 2024SARATR-X: Toward Building A Foundation Model for SAR Target Recognitioncited by 25
38 more
  1. 2024ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation Modelscited by 24
  2. 2024CHOICE: Benchmarking the Remote Sensing Capabilities of Large Vision-Language Modelscited by 22
  3. 2024An LLM Agent for Automatic Geospatial Data Analysiscited by 21
  4. 2025RingMo-Agent: A Unified Remote Sensing Foundation Model for Multi-Platform and Multi-Modal Reasoningcited by 20
  5. 2025Geo-R1: Improving Few-Shot Geospatial Referring Expression Understanding with Reinforcement Fine-Tuningcited by 20
  6. 2023Bootstrapping Interactive Image-Text Alignment for Remote Sensing Image Captioningcited by 18
  7. 2025Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectivescited by 18
  8. 2025SARLANG-1M: A Benchmark for Vision-Language Modeling in SAR Image Understandingcited by 16
  9. 2024RS-MoE: A Vision-Language Model with Mixture of Experts for Remote Sensing Image Captioning and Visual Question Answeringcited by 15
  10. 2025REOBench: Benchmarking Robustness of Earth Observation Foundation Modelscited by 15
  11. 2023When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence Systemcited by 13
  12. 2023PatFig: Generating Short and Long Captions for Patent Figurescited by 12
  13. 2026Foundation Models in Remote Sensing: Evolving from Unimodality to Multimodalitycited by 12
  14. 2024SeaMo: A Season-Aware Multimodal Foundation Model for Remote Sensingcited by 11
  15. 2023LiT-4-RSVQA: Lightweight Transformer-based Visual Question Answering in Remote Sensingcited by 10
  16. 2025Semi-supervised Semantic Segmentation for Remote Sensing Images via Multi-scale Uncertainty Consistency and Cross-Teacher-Student Attentioncited by 10
  17. 2026GeoReason: Aligning Thinking And Answering In Remote Sensing Vision-Language Models Via Logical Consistency Reinforcement Learningcited by 10
  18. 2024Enhancing Remote Sensing Vision-Language Models for Zero-Shot Scene Classificationcited by 8
  19. 2024Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT Modelscited by 8
  20. 2025OpenFACADES: An Open Framework for Architectural Caption and Attribute Data Enrichment via Street View Imagerycited by 8
  21. 2025GAIA: A Global, Multi-modal, Multi-scale Vision-Language Dataset for Remote Sensing Image Analysiscited by 7
  22. 2023Stable Segment Anything Modelcited by 6
  23. 2023MetaSegNet: Metadata-collaborative Vision-Language Representation Learning for Semantic Segmentation of Remote Sensing Imagescited by 6
  24. 2024ImageRAG: Enhancing Ultra High Resolution Remote Sensing Imagery Analysis with ImageRAGcited by 6
  25. 2025GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensingcited by 6
  26. 2025Remote Sensing Retrieval-Augmented Generation: Bridging Remote Sensing Imagery and Comprehensive Knowledge with a Multi-Modal Dataset and Retrieval-Augmented Generation Modelcited by 6
  27. 2025Asking like Socrates: Socrates helps VLMs understand remote sensing imagescited by 6
  28. 2026GRASP: Guided Region-Aware Sparse Prompting for Adapting MLLMs to Remote Sensingcited by 6
  29. 2025Visual Instruction Bottleneck Tuningcited by 5
  30. 2024Automated Floodwater Depth Estimation Using Large Multimodal Model for Rapid Flood Mappingcited by 4
  31. 2024Deep Learning for Spatio-Temporal Fusion in Land Surface Temperature Estimation: A Comprehensive Survey, Experimental Analysis, and Future Trendscited by 4
  32. 2025Generalization-Enhanced Few-Shot Object Detection in Remote Sensingcited by 4
  33. 2025DGTRSD & DGTRS-CLIP: A Dual-Granularity Remote Sensing Image-Text Dataset and Vision Language Foundation Model for Alignmentcited by 4
  34. 2025CartoAgent: a multimodal large language model-powered multi-agent cartographic framework for map style transfer and evaluationcited by 4
  35. 2025ECVL-ROUTER: Scenario-Aware Routing for Vision-Language Modelscited by 4
  36. 2024Solid Waste Detection, Monitoring and Mapping in Remote Sensing Images: A Surveycited by 3
  37. 2024Cross-sensor self-supervised training and alignment for remote sensingcited by 3
  38. 2024MGIMM: Multi-Granularity Instruction Multimodal Model for Attribute-Guided Remote Sensing Image Detailed Descriptioncited by 3

50 most cited of 93 All 93 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2024Advancements in Visual Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques
  2. 2026Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?
  3. 2024Remote Sensing ChatGPT: Solving Remote Sensing Tasks with ChatGPT and Visual Models
  4. 2024From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing
  5. 2024Pushing the Limits of Vision-Language Models in Remote Sensing without Human Annotations
  6. 2024SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Model
  7. 2023GeoChat: Grounded Large Vision-Language Model for Remote Sensing
  8. 2025Falcon: A Remote Sensing Vision-Language Foundation Model (Technical Report)