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xView: Objects in Context in Overhead Imagery

arXiv 1802.07856 ↗First posted 22 Feb 2018cs.CVcited by 145

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Abstract (arXiv)

We introduce a new large-scale dataset for the advancement of object detection techniques and overhead object detection research. This satellite imagery dataset enables research progress pertaining to four key computer vision frontiers. We utilize a novel process for geospatial category detection and bounding box annotation with three stages of quality control. Our data is collected from WorldView-3 satellites at 0.3m ground sample distance, providing higher resolution imagery than most public satellite imagery datasets. We compare xView to other object detection datasets in both natural and overhead imagery domains and then provide a baseline analysis using the Single Shot MultiBox Detector. xView is one of the largest and most diverse publicly available object-detection datasets to date, with over 1 million objects across 60 classes in over 1,400 km^2 of imagery.

Key facts. Cited by 145 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 26; 2022: 23; 2023: 17; 2024: 18; 2025: 31; 2026: 30.

145 papers.

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  1. 2022SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagerycited by 402
  2. 2021Object Detection in Aerial Images: A Large-Scale Benchmark and Challengescited by 202
  3. 2021FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagerycited by 143
  4. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagerycited by 130
  5. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
  6. 2022Slicing Aided Hyper Inference and Fine-tuning for Small Object Detectioncited by 101
  7. 2024Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodologycited by 92
  8. 2023On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligencecited by 88
  9. 2021Self-Supervised Pretraining Improves Self-Supervised Pretrainingcited by 81
  10. 2021Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detectioncited by 67
  11. 2024MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretrainingcited by 66
  12. 2021The Multi-Temporal Urban Development SpaceNet Datasetcited by 62
38 more
  1. 2022Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmarkcited by 56
  2. 2021SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learningcited by 53
  3. 2024Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Communitycited by 50
  4. 2022Aerial Vision-and-Dialog Navigationcited by 48
  5. 2025UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobilitycited by 48
  6. 2024CityNav: A Large-Scale Dataset for Real-World Aerial Navigationcited by 40
  7. 2024GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilotscited by 27
  8. 2022xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagerycited by 25
  9. 2023Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advancescited by 20
  10. 2025Multi-Agent Geospatial Copilots for Remote Sensing Workflowscited by 20
  11. 2025A Survey on Remote Sensing Foundation Models: From Vision to Multimodalitycited by 18
  12. 2021Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmarkcited by 17
  13. 2024Evaluating Tool-Augmented Agents in Remote Sensing Platformscited by 17
  14. 2021IS-COUNT: Large-scale Object Counting from Satellite Images with Covariate-based Importance Samplingcited by 14
  15. 2022A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillancecited by 14
  16. 2021Visual and Object Geo-localization: A Comprehensive Surveycited by 13
  17. 2022Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensingcited by 13
  18. 2024Object Detectors in the Open Environment: Challenges, Solutions, and Outlookcited by 13
  19. 2025LISAT: Language-Instructed Segmentation Assistant for Satellite Imagerycited by 13
  20. 20213D Instance Segmentation of MVS Buildingscited by 12
  21. 2025Aerial Vision-and-Language Navigation with Grid-based View Selection and Map Constructioncited by 12
  22. 2024OpenSatMap: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Constructioncited by 11
  23. 2025EarthView: A Large Scale Remote Sensing Dataset for Self-Supervisioncited by 11
  24. 2024Zero-Shot Aerial Object Detection with Visual Description Regularizationcited by 10
  25. 2022In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?cited by 9
  26. 2023CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understandingcited by 9
  27. 2025OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Imagescited by 9
  28. 2021Oriented Bounding Boxes for Small and Freely Rotated Objectscited by 8
  29. 2022A Visual Active Search Framework for Geospatial Explorationcited by 8
  30. 2023A Partially Supervised Reinforcement Learning Framework for Visual Active Searchcited by 8
  31. 2024Source-free Domain Adaptive Object Detection in Remote Sensing Imagescited by 8
  32. 2024Panoptic Perception: A Novel Task and Fine-grained Dataset for Universal Remote Sensing Image Interpretationcited by 8
  33. 2024MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generationcited by 8
  34. 2021NTIRE 2021 Multi-modal Aerial View Object Classification Challengecited by 7
  35. 2023Oriented object detection in optical remote sensing images using deep learning: a surveycited by 7
  36. 2021Overhead MNIST: A Benchmark Satellite Datasetcited by 6
  37. 2024FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature Compressioncited by 6
  38. 2025Advancing Earth Observation: A Survey on AI-Powered Image Processing in Satellitescited by 6

50 most cited of 145 All 145 (JSON)