mlsanityData to 7 Oct 2026

The State of Aerial Surveillance: A Survey

arXiv 2201.03080 ↗First posted 9 Jan 2022cs.CV cs.AI cs.CRcited by 20

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Abstract (arXiv)

The rapid emergence of airborne platforms and imaging sensors are enabling new forms of aerial surveillance due to their unprecedented advantages in scale, mobility, deployment and covert observation capabilities. This paper provides a comprehensive overview of human-centric aerial surveillance tasks from a computer vision and pattern recognition perspective. It aims to provide readers with an in-depth systematic review and technical analysis of the current state of aerial surveillance tasks using drones, UAVs and other airborne platforms. The main object of interest is humans, where single or multiple subjects are to be detected, identified, tracked, re-identified and have their behavior analyzed. More specifically, for each of these four tasks, we first discuss unique challenges in performing these tasks in an aerial setting compared to a ground-based setting. We then review and analyze the aerial datasets publicly available for each task, and delve deep into the approaches in the aerial literature and investigate how they presently address the aerial challenges. We conclude the paper with discussion on the missing gaps and open research questions to inform future research avenues.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 70 of its 191 references that are in the map. First posted on arXiv 9 Jan 2022.

Builds on

70 of 191 references.

References · 70

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 9; 2024: 6; 2025: 3; 2026: 1.

20 papers.

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  1. 2024AG-ReID.v2: Bridging Aerial and Ground Views for Person Re-identificationcited by 19
  2. 2023Aerial-Ground Person Re-IDcited by 18
  3. 2023Synthetic-to-Real Domain Adaptation for Action Recognition: A Dataset and Baseline Performancescited by 15
  4. 2023SkyScenes: A Synthetic Dataset for Aerial Scene Understandingcited by 12
  5. 2025AG-VPReID: A Challenging Large-Scale Benchmark for Aerial-Ground Video-based Person Re-Identificationcited by 12
  6. 2023Survey on video anomaly detection in dynamic scenes with moving camerascited by 10
  7. 2023AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoningcited by 8
  8. 2023PMI Sampler: Patch Similarity Guided Frame Selection for Aerial Action Recognitioncited by 7
  9. 2022Differentiable Frequency-based Disentanglement for Aerial Video Action Recognitioncited by 4
  10. 2023MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognitioncited by 4
  11. 2023NOMAD: A Natural, Occluded, Multi-scale Aerial Dataset, for Emergency Response Scenarioscited by 4
  12. 2024Motion Segmentation for Neuromorphic Aerial Surveillancecited by 2
8 more
  1. 2024UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Trackingcited by 2
  2. 2025AG-VPReID 2025: Aerial-Ground Video-based Person Re-identification Challenge Resultscited by 2
  3. 2023Deep Learning-Based Object Detection in Maritime Unmanned Aerial Vehicle Imagery: Review and Experimental Comparisonscited by 1
  4. 2026VReID-XFD: Video-based Person Re-identification at Extreme Far Distance Challenge Resultscited by 1
  5. 2024FALCON: Future-Aware Learning with Contextual Object-Centric Pretraining for UAV Action Recognitioncited by 0
  6. 2024Revisiting the Role of Texture in 3D Person Re-identificationcited by 0
  7. 2024Psych-Occlusion: Using Visual Psychophysics for Aerial Detection of Occluded Persons during Search and Rescuecited by 0
  8. 2025RedunCut: Measurement-Driven Sampling and Accuracy Performance Modeling for Low-Cost Live Video Analyticscited by 0