mlsanityData to 7 Oct 2026

DOTA: A Large-scale Dataset for Object Detection in Aerial Images

arXiv 1711.10398 ↗First posted 28 Nov 2017cs.CVcited by 622

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Cited by 47 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge variation in the scale, orientation and shape of the object instances on the earth's surface, but also due to the scarcity of well-annotated datasets of objects in aerial scenes. To advance object detection research in Earth Vision, also known as Earth Observation and Remote Sensing, we introduce a large-scale Dataset for Object deTection in Aerial images (DOTA). To this end, we collect 2806 aerial images from different sensors and platforms. Each image is of the size about 4000-by-4000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes. These DOTA images are then annotated by experts in aerial image interpretation using 15 common object categories. The fully annotated DOTA images contains 188,282 instances, each of which is labeled by an arbitrary (8 d.o.f.) quadrilateral To build a baseline for object detection in Earth Vision, we evaluate state-of-the-art object detection algorithms on DOTA. Experiments demonstrate that DOTA well represents real Earth Vision applications and are quite challenging.

Key facts. Cited by 622 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Nov 2017.

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Citing papers per year: 2021: 89; 2022: 93; 2023: 108; 2024: 109; 2025: 113; 2026: 110.

622 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. 2021Oriented R-CNN for Object Detectioncited by 230
  4. 2021Object Detection in Aerial Images: A Large-Scale Benchmark and Challengescited by 202
  5. 2021ReDet: A Rotation-equivariant Detector for Aerial Object Detectioncited by 202
  6. 2021Embracing Single Stride 3D Object Detector with Sparse Transformercited by 193
  7. 2022RTMDet: An Empirical Study of Designing Real-Time Object Detectorscited by 192
  8. 2022Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cutcited by 166
  9. 2022SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understandingcited by 164
  10. 2021Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Losscited by 156
  11. 2023RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensingcited by 150
  12. 2022Advancing Plain Vision Transformer Towards Remote Sensing Foundation Modelcited by 149
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  1. 2023A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAScited by 149
  2. 2021FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagerycited by 143
  3. 2023Foundation Models for Generalist Geospatial Artificial Intelligencecited by 143
  4. 2024VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Taskscited by 136
  5. 2024LHRS-Bot: Empowering Remote Sensing with VGI-Enhanced Large Multimodal Language Modelcited by 133
  6. 2021Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergencecited by 130
  7. 2022MMRotate: A Rotated Object Detection Benchmark using PyTorchcited by 115
  8. 2024SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Modelcited by 112
  9. 2022TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cutcited by 111
  10. 2022An Empirical Study of Remote Sensing Pretrainingcited by 105
  11. 2021Anchor-free Oriented Proposal Generator for Object Detectioncited by 104
  12. 2021Oriented RepPoints for Aerial Object Detectioncited by 102
  13. 2023Large Selective Kernel Network for Remote Sensing Object Detectioncited by 98
  14. 2024Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Wantcited by 98
  15. 2022High-Quality Entity Segmentationcited by 93
  16. 2021Class-agnostic Object Detection with Multi-modal Transformercited by 85
  17. 2022DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentationcited by 78
  18. 2022The KFIoU Loss for Rotated Object Detectioncited by 73
  19. 2024HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Modelcited by 72
  20. 2024TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Datacited by 69
  21. 2024MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretrainingcited by 66
  22. 2025Detect Anything via Next Point Predictioncited by 66
  23. 2021Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environmentscited by 65
  24. 2022Few Could Be Better Than All: Feature Sampling and Grouping for Scene Text Detectioncited by 65
  25. 2023A Billion-scale Foundation Model for Remote Sensing Imagescited by 62
  26. 2022Transformers in Remote Sensing: A Surveycited by 61
  27. 2021SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Watercited by 59
  28. 2021Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Codingcited by 58
  29. 2023C2Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detectioncited by 57
  30. 2022Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmarkcited by 56
  31. 2023EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolutioncited by 56
  32. 2022AO2-DETR: Arbitrary-Oriented Object Detection Transformercited by 55
  33. 2021Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Typescited by 54
  34. 2021Transferability Estimation using Bhattacharyya Class Separabilitycited by 53
  35. 2021A Normalized Gaussian Wasserstein Distance for Tiny Object Detectioncited by 52
  36. 2024Poly Kernel Inception Network for Remote Sensing Detectioncited by 52
  37. 2023Adaptive Rotated Convolution for Rotated Object Detectioncited by 51
  38. 2024Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Communitycited by 50

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