Vision-Based Anti Unmanned Aerial Technology: Opportunities and Challenges

• URL: http://arxiv.org/abs/2507.10006v1
• Date: Mon, 14 Jul 2025 07:39:55 GMT
• Title: Vision-Based Anti Unmanned Aerial Technology: Opportunities and Challenges
• Authors: Guanghai Ding, Yihua Ren, Yuting Liu, Qijun Zhao, Shuiwang Li,
• Abstract summary: This paper reviews the characteristics and current challenges of Anti-UAV detection and tracking technologies.<n>It analyzes the major vision-based and vision-fusion-based Anti-UAV detection and tracking algorithms proposed in recent years.
• Score: 9.131137470558158
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the rapid advancement of UAV technology and its extensive application in various fields such as military reconnaissance, environmental monitoring, and logistics, achieving efficient and accurate Anti-UAV tracking has become essential. The importance of Anti-UAV tracking is increasingly prominent, especially in scenarios such as public safety, border patrol, search and rescue, and agricultural monitoring, where operations in complex environments can provide enhanced security. Current mainstream Anti-UAV tracking technologies are primarily centered around computer vision techniques, particularly those that integrate multi-sensor data fusion with advanced detection and tracking algorithms. This paper first reviews the characteristics and current challenges of Anti-UAV detection and tracking technologies. Next, it investigates and compiles several publicly available datasets, providing accessible links to support researchers in efficiently addressing related challenges. Furthermore, the paper analyzes the major vision-based and vision-fusion-based Anti-UAV detection and tracking algorithms proposed in recent years. Finally, based on the above research, this paper outlines future research directions, aiming to provide valuable insights for advancing the field.

Related papers

• SoK: Advances and Open Problems in Web Tracking [71.54586748169943]
  Web tracking is a pervasive and opaque practice that enables personalized advertising, and conversion tracking.<n>Web tracking is undergoing a once-in-a-generation transformation driven by shifts in the advertising industry, the adoption of anti-tracking countermeasures by browsers, and the growing enforcement of emerging privacy regulations.<n>This Systematization of Knowledge (SoK) aims to consolidate and synthesize this wide-ranging research, offering a comprehensive overview of the technical mechanisms, countermeasures, and regulations that shape the modern and rapidly evolving web tracking landscape.
  arXiv  Detail & Related papers  (2025-06-16T23:30:54Z)
• Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions [22.160090947392344]
  Unmanned Aerial Vehicles (UAVs) are indispensable for infrastructure inspection, surveillance, and related tasks, yet they also introduce critical security challenges.<n>This survey provides a wide-ranging examination of the anti-UAV domain, centering on three core objectives-classification, detection, and tracking.<n>We systematically evaluate state-of-the-art solutions across both single-modality and multi-sensor pipelines.
  arXiv  Detail & Related papers  (2025-04-16T10:58:33Z)
• UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility [33.73170899086857]
  Low-altitude mobility, exemplified by unmanned aerial vehicles (UAVs), has introduced transformative advancements across various domains.<n>This paper explores the integration of large language models (LLMs) and UAVs.<n>It categorizes and analyzes key tasks and application scenarios where UAVs and LLMs converge.
  arXiv  Detail & Related papers  (2025-01-04T17:32:12Z)
• Networking Systems for Video Anomaly Detection: A Tutorial and Survey [55.28514053969056]
  Video Anomaly Detection (VAD) is a fundamental research task within the Artificial Intelligence (AI) community.<n>With the advancements in deep learning and edge computing, VAD has made significant progress.<n>This article offers an exhaustive tutorial for novices in NSVAD.
  arXiv  Detail & Related papers  (2024-05-16T02:00:44Z)
• A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges [0.6827423171182153]
  The study examines how AI plays a role in enabling navigation, detecting and tracking objects, monitoring wildlife, enhancing precision agriculture, facilitating rescue operations, conducting surveillance activities, and establishing communication among UAVs using environmentally conscious computing techniques. While envisioning possibilities, it also takes a look at ethical considerations, safety concerns, regulatory frameworks to be established, and the responsible deployment of AI-enhanced UAV systems.
  arXiv  Detail & Related papers  (2023-10-25T04:52:16Z)
• Evidential Detection and Tracking Collaboration: New Problem, Benchmark and Algorithm for Robust Anti-UAV System [56.51247807483176]
  Unmanned Aerial Vehicles (UAVs) have been widely used in many areas, including transportation, surveillance, and military. Previous works have simplified such an anti-UAV task as a tracking problem, where prior information of UAVs is always provided. In this paper, we first formulate a new and practical anti-UAV problem featuring the UAVs perception in complex scenes without prior UAVs information.
  arXiv  Detail & Related papers  (2023-06-27T19:30:23Z)
• Investigation of UAV Detection in Images with Complex Backgrounds and Rainy Artifacts [20.20609511526255]
  Vision-based object detection methods have been developed for UAV detection. UAV detection in images with complex backgrounds and weather artifacts like rain has yet to be reasonably studied. This work also focuses on benchmarking state-of-the-art object detection models.
  arXiv  Detail & Related papers  (2023-05-25T19:54:33Z)
• The State of Aerial Surveillance: A Survey [62.198765910573556]
  This paper provides a comprehensive overview of human-centric aerial surveillance tasks from a computer vision and pattern recognition perspective. 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.
  arXiv  Detail & Related papers  (2022-01-09T20:13:27Z)
• Deep Learning for UAV-based Object Detection and Tracking: A Survey [25.34399619170044]
  Unmanned aerial vehicle (UAV) has recently become a hotspot across the fields of computer vision (CV) and remote sensing (RS) Inspired by recent success of deep learning (DL), many advanced object detection and tracking approaches have been widely applied to various UAV-related tasks. This paper provides a comprehensive survey on the research progress and prospects of DL-based UAV object detection and tracking methods.
  arXiv  Detail & Related papers  (2021-10-25T04:43:24Z)
• Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking [59.06167734555191]
  Unmanned Aerial Vehicle (UAV) offers lots of applications in both commerce and recreation. We consider the task of tracking UAVs, providing rich information such as location and trajectory. We propose a dataset, Anti-UAV, with more than 300 video pairs containing over 580k manually annotated bounding boxes.
  arXiv  Detail & Related papers  (2021-01-21T07:00:15Z)
• Artificial Intelligence for UAV-enabled Wireless Networks: A Survey [72.10851256475742]
  Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for the next-generation wireless communication networks. Artificial intelligence (AI) is growing rapidly nowadays and has been very successful. We provide a comprehensive overview of some potential applications of AI in UAV-based networks.
  arXiv  Detail & Related papers  (2020-09-24T07:11:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.