mlsanityData to 7 Oct 2026

AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classification

arXiv 1608.05167 ↗First posted 18 Aug 2016cs.CVcited by 343

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Cited by 64 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Aerial scene classification, which aims to automatically label an aerial image with a specific semantic category, is a fundamental problem for understanding high-resolution remote sensing imagery. In recent years, it has become an active task in remote sensing area and numerous algorithms have been proposed for this task, including many machine learning and data-driven approaches. However, the existing datasets for aerial scene classification like UC-Merced dataset and WHU-RS19 are with relatively small sizes, and the results on them are already saturated. This largely limits the development of scene classification algorithms. This paper describes the Aerial Image Dataset (AID): a large-scale dataset for aerial scene classification. The goal of AID is to advance the state-of-the-arts in scene classification of remote sensing images. For creating AID, we collect and annotate more than ten thousands aerial scene images. In addition, a comprehensive review of the existing aerial scene classification techniques as well as recent widely-used deep learning methods is given. Finally, we provide a performance analysis of typical aerial scene classification and deep learning approaches on AID, which can be served as the baseline results on this benchmark.

Key facts. Cited by 343 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Aug 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 23; 2022: 36; 2023: 51; 2024: 67; 2025: 101; 2026: 65.

343 papers.

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  1. 2023RemoteCLIP: A Vision Language Foundation Model for Remote Sensingcited by 357
  2. 2023GeoChat: Grounded Large Vision-Language Model for Remote Sensingcited by 320
  3. 2021Object Detection in Aerial Images: A Large-Scale Benchmark and Challengescited by 202
  4. 2023SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagerycited by 202
  5. 2024EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domaincited by 181
  6. 2022SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understandingcited by 164
  7. 2023RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensingcited by 150
  8. 2022Advancing Plain Vision Transformer Towards Remote Sensing Foundation Modelcited by 149
  9. 2024LHRS-Bot: Empowering Remote Sensing with VGI-Enhanced Large Multimodal Language Modelcited by 133
  10. 2023SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensingcited by 123
  11. 2021Towards artificial general intelligence via a multimodal foundation modelcited by 112
  12. 2022An Empirical Study of Remote Sensing Pretrainingcited by 105
38 more
  1. 2024SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understandingcited by 101
  2. 2024RSMamba: Remote Sensing Image Classification with State Space Modelcited by 95
  3. 2023Vision-Language Models in Remote Sensing: Current Progress and Future Trendscited by 93
  4. 2023On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligencecited by 88
  5. 2024EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialoguescited by 81
  6. 2024TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Datacited by 69
  7. 2021Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environmentscited by 65
  8. 2022Transformers in Remote Sensing: A Surveycited by 61
  9. 2021Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Codingcited by 58
  10. 2023EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolutioncited by 56
  11. 2023EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question Answeringcited by 51
  12. 2024Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Communitycited by 50
  13. 2024Cross-Scale MAE: A Tale of Multi-Scale Exploitation in Remote Sensingcited by 47
  14. 2024Frequency-Assisted Mamba for Remote Sensing Image Super-Resolutioncited by 47
  15. 2024RS-Agent: Automating Remote Sensing Tasks through Intelligent Agentcited by 46
  16. 2024LSKNet: A Foundation Lightweight Backbone for Remote Sensingcited by 44
  17. 2025ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Taskscited by 41
  18. 2022EarthNets: Empowering AI in Earth Observationcited by 40
  19. 2022From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Datacited by 38
  20. 2024Towards Vision-Language Geo-Foundation Model: A Surveycited by 36
  21. 2022TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learningcited by 35
  22. 2025DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage Assessment and Responsecited by 35
  23. 2023ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain Adaptationcited by 34
  24. 2023DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restorationcited by 32
  25. 2023Model Spider: Learning to Rank Pre-Trained Models Efficientlycited by 32
  26. 2022Enabling Country-Scale Land Cover Mapping with Meter-Resolution Satellite Imagerycited by 31
  27. 2021Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systemscited by 29
  28. 2023S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captionscited by 29
  29. 2024EarthMarker: A Visual Prompting Multi-modal Large Language Model for Remote Sensingcited by 29
  30. 2021Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Datacited by 26
  31. 2025SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensingcited by 26
  32. 2021Self-supervised Audiovisual Representation Learning for Remote Sensing Datacited by 24
  33. 2022Universal Adversarial Examples in Remote Sensing: Methodology and Benchmarkcited by 24
  34. 2022Self-supervised remote sensing feature learning: Learning Paradigms, Challenges, and Future Workscited by 24
  35. 2022Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domaincited by 22
  36. 2023Domain-Controlled Prompt Learningcited by 22
  37. 2024Masked Angle-Aware Autoencoder for Remote Sensing Imagescited by 22
  38. 2023CL-MAE: Curriculum-Learned Masked Autoencoderscited by 21

50 most cited of 343 All 343 (JSON)