mlsanityData to 7 Oct 2026

Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances

arXiv 2309.06751 ↗First posted 13 Sep 2023cs.CVcited by 20

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Abstract (arXiv)

Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received longstanding attention. In recent years, deep learning techniques have demonstrated robust feature representation capabilities and led to a big leap in the development of RSOD techniques. In this era of rapid technical evolution, this review aims to present a comprehensive review of the recent achievements in deep learning based RSOD methods. More than 300 papers are covered in this review. We identify five main challenges in RSOD, including multi-scale object detection, rotated object detection, weak object detection, tiny object detection, and object detection with limited supervision, and systematically review the corresponding methods developed in a hierarchical division manner. We also review the widely used benchmark datasets and evaluation metrics within the field of RSOD, as well as the application scenarios for RSOD. Future research directions are provided for further promoting the research in RSOD.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 82 of its 361 references that are in the map. First posted on arXiv 13 Sep 2023.

Builds on

82 of 361 references.

References · 82

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  2. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
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38 more
  1. 2019Selective Kernel Networkscited by 401
  2. 2018Deep Learning for Generic Object Detection: A Surveycited by 392
  3. 2019Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmarkcited by 339
  4. 2017Functional Map of the Worldcited by 338
  5. 2019Libra R-CNN: Towards Balanced Learning for Object Detectioncited by 255
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  12. 2021Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Losscited by 156
  13. 2022Advancing Plain Vision Transformer Towards Remote Sensing Foundation Modelcited by 149
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  15. 2021FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagerycited by 143
  16. 2017Receptive Field Block Net for Accurate and Fast Object Detectioncited by 140
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  18. 2021Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergencecited by 130
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  20. 2020More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classificationcited by 126
  21. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
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Citing papers per year: 2023: 1; 2024: 5; 2025: 8; 2026: 6.

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  1. 2024Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Wantcited by 98
  2. 2024Remote Sensing ChatGPT: Solving Remote Sensing Tasks with ChatGPT and Visual Modelscited by 30
  3. 2023Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher Learningcited by 22
  4. 2024Brain-Inspired Online Adaptation for Remote Sensing with Spiking Neural Networkcited by 8
  5. 2024MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generationcited by 8
  6. 2025Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detectioncited by 6
  7. 2024Exploiting Unlabeled Data with Multiple Expert Teachers for Open Vocabulary Aerial Object Detection and Its Orientation Adaptationcited by 4
  8. 2026Fourier Angle Alignment for Oriented Object Detection in Remote Sensingcited by 3
  9. 2025Remote Sensing-Oriented World Modelcited by 2
  10. 2025Remote Sensing Image Intelligent Interpretation with the Language-Centered Perspective: Principles, Methods and Challengescited by 1
  11. 2025Integrating Machine Learning into Belief-Desire-Intention Agents: Current Advances and Open Challengescited by 1
  12. 2025DiffMOD: Progressive Diffusion Point Denoising for Moving Object Detection in Remote Sensingcited by 0
8 more
  1. 2025MVT: Mask-Grounded Vision-Language Models for Taxonomy-Aligned Land-Cover Taggingcited by 0
  2. 2025Scale-Aware Relay and Scale-Adaptive Loss for Tiny Object Detection in Aerial Imagescited by 0
  3. 2025Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognitioncited by 0
  4. 2026FGAA-FPN: Foreground-Guided Angle-Aware Feature Pyramid Network for Oriented Object Detectioncited by 0
  5. 2026PASTE: Physics-Aware Scattering Topology Embedding Framework for SAR Object Detectioncited by 0
  6. 2026HMR-Net: Hierarchical Modular Routing for Cross-Domain Object Detection in Aerial Imagescited by 0
  7. 2026Diagnosing Aerial-View Object Detectors with Foundational Image Generative Modelscited by 0
  8. 2026Hyperbolic Geometry for Open-World Object Detection in Remote Sensing Imagerycited by 0