mlsanityData to 7 Oct 2026

Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark

arXiv 1909.00133 ↗First posted 31 Aug 2019cs.CVcited by 339

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Cited by 39 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Substantial efforts have been devoted more recently to presenting various methods for object detection in optical remote sensing images. However, the current survey of datasets and deep learning based methods for object detection in optical remote sensing images is not adequate. Moreover, most of the existing datasets have some shortcomings, for example, the numbers of images and object categories are small scale, and the image diversity and variations are insufficient. These limitations greatly affect the development of deep learning based object detection methods. In the paper, we provide a comprehensive review of the recent deep learning based object detection progress in both the computer vision and earth observation communities. Then, we propose a large-scale, publicly available benchmark for object DetectIon in Optical Remote sensing images, which we name as DIOR. The dataset contains 23463 images and 192472 instances, covering 20 object classes. The proposed DIOR dataset 1) is large-scale on the object categories, on the object instance number, and on the total image number; 2) has a large range of object size variations, not only in terms of spatial resolutions, but also in the aspect of inter- and intra-class size variability across objects; 3) holds big variations as the images are obtained with different imaging conditions, weathers, seasons, and image quality; and 4) has high inter-class similarity and intra-class diversity. The proposed benchmark can help the researchers to develop and validate their data-driven methods. Finally, we evaluate several state-of-the-art approaches on our DIOR dataset to establish a baseline for future research.

Key facts. Cited by 339 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Aug 2019.

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Citing papers per year: 2021: 26; 2022: 37; 2023: 38; 2024: 71; 2025: 91; 2026: 76.

339 papers.

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  1. 2023RemoteCLIP: A Vision Language Foundation Model for Remote Sensingcited by 357
  2. 2021Oriented R-CNN for Object Detectioncited by 230
  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. 2023RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Modelcited by 180
  6. 2022Advancing Plain Vision Transformer Towards Remote Sensing Foundation Modelcited by 149
  7. 2021FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagerycited by 143
  8. 2022RSVG: Exploring Data and Models for Visual Grounding on Remote Sensing Datacited by 121
  9. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
  10. 2024VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understandingcited by 116
  11. 2024SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Modelcited by 112
  12. 2022An Empirical Study of Remote Sensing Pretrainingcited by 105
38 more
  1. 2021Anchor-free Oriented Proposal Generator for Object Detectioncited by 104
  2. 2021Oriented RepPoints for Aerial Object Detectioncited by 102
  3. 2025TerraMind: Large-Scale Generative Multimodality for Earth Observationcited by 101
  4. 2024Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Wantcited by 98
  5. 2023Vision-Language Models in Remote Sensing: Current Progress and Future Trendscited by 93
  6. 2021Mean-Shifted Contrastive Loss for Anomaly Detectioncited by 87
  7. 2024EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialoguescited by 81
  8. 2022The KFIoU Loss for Rotated Object Detectioncited by 73
  9. 2024HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Modelcited by 72
  10. 2024TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Datacited by 69
  11. 2024MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretrainingcited by 66
  12. 2024Many-Shot In-Context Learning in Multimodal Foundation Modelscited by 64
  13. 2024PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Modelscited by 62
  14. 2022Transformers in Remote Sensing: A Surveycited by 61
  15. 2023RRSIS: Referring Remote Sensing Image Segmentationcited by 59
  16. 2022Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmarkcited by 56
  17. 2023EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolutioncited by 56
  18. 2024Poly Kernel Inception Network for Remote Sensing Detectioncited by 52
  19. 2024Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Communitycited by 50
  20. 2024GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Taskscited by 50
  21. 2023CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understandingcited by 48
  22. 2025UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobilitycited by 48
  23. 2024SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detectioncited by 47
  24. 2024Frequency-Assisted Mamba for Remote Sensing Image Super-Resolutioncited by 47
  25. 2024RS-Agent: Automating Remote Sensing Tasks through Intelligent Agentcited by 46
  26. 2025Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Modelcited by 46
  27. 2023Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detectioncited by 43
  28. 2024Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detectorcited by 43
  29. 2022EarthNets: Empowering AI in Earth Observationcited by 40
  30. 2024Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation datacited by 39
  31. 2022From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Datacited by 38
  32. 2023SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Modelcited by 38
  33. 2025RemoteSAM: Towards Segment Anything for Earth Observationcited by 38
  34. 2022H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detectioncited by 36
  35. 2021RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing Imagescited by 34
  36. 2021Deep Learning for UAV-based Object Detection and Tracking: A Surveycited by 33
  37. 2023ARS-DETR: Aspect Ratio-Sensitive Detection Transformer for Aerial Oriented Object Detectioncited by 32
  38. 2024AeroGen: Enhancing Remote Sensing Object Detection with Diffusion-Driven Data Generationcited by 32

50 most cited of 339 All 339 (JSON)