CST Anti-UAV: A Thermal Infrared Benchmark for Tiny UAV Tracking in Complex Scenes

• URL: http://arxiv.org/abs/2507.23473v1
• Date: Thu, 31 Jul 2025 11:53:21 GMT
• Title: CST Anti-UAV: A Thermal Infrared Benchmark for Tiny UAV Tracking in Complex Scenes
• Authors: Bin Xie, Congxuan Zhang, Fagan Wang, Peng Liu, Feng Lu, Zhen Chen, Weiming Hu,
• Abstract summary: We present a new thermal infrared dataset specifically designed for Single Object Tracking (SOT) in Complex Scenes with Tiny UAVs (CST)<n>It contains 220 video sequences with over 240k high-quality bounding box annotations, highlighting two key properties: a significant number of tiny-sized UAV targets and the diverse and complex scenes.<n>CST Anti-UAV is the first dataset to incorporate complete manual frame-level attribute annotations, enabling precise evaluations under varied challenges.
• Score: 35.983551600618476
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The widespread application of Unmanned Aerial Vehicles (UAVs) has raised serious public safety and privacy concerns, making UAV perception crucial for anti-UAV tasks. However, existing UAV tracking datasets predominantly feature conspicuous objects and lack diversity in scene complexity and attribute representation, limiting their applicability to real-world scenarios. To overcome these limitations, we present the CST Anti-UAV, a new thermal infrared dataset specifically designed for Single Object Tracking (SOT) in Complex Scenes with Tiny UAVs (CST). It contains 220 video sequences with over 240k high-quality bounding box annotations, highlighting two key properties: a significant number of tiny-sized UAV targets and the diverse and complex scenes. To the best of our knowledge, CST Anti-UAV is the first dataset to incorporate complete manual frame-level attribute annotations, enabling precise evaluations under varied challenges. To conduct an in-depth performance analysis for CST Anti-UAV, we evaluate 20 existing SOT methods on the proposed dataset. Experimental results demonstrate that tracking tiny UAVs in complex environments remains a challenge, as the state-of-the-art method achieves only 35.92% state accuracy, much lower than the 67.69% observed on the Anti-UAV410 dataset. These findings underscore the limitations of existing benchmarks and the need for further advancements in UAV tracking research. The CST Anti-UAV benchmark is about to be publicly released, which not only fosters the development of more robust SOT methods but also drives innovation in anti-UAV systems.

Related papers

• More Clear, More Flexible, More Precise: A Comprehensive Oriented Object Detection benchmark for UAV [58.89234732689013]
  CODrone is a comprehensive oriented object detection dataset for UAVs that accurately reflects real-world conditions.<n>It also serves as a new benchmark designed to align with downstream task requirements.<n>We conduct a series of experiments based on 22 classical or SOTA methods to rigorously evaluate CODrone.
  arXiv  Detail & Related papers  (2025-04-28T17:56:02Z)
• Unsupervised UAV 3D Trajectories Estimation with Sparse Point Clouds [18.48877348628721]
  This paper presents a cost-effective, unsupervised UAV detection method using spatial-temporal sequence processing.<n>Our solution placed 4th in the CVPR 2024 UG2+ Challenge, demonstrating its practical effectiveness.<n>We plan to open-source all designs, code, and sample data for the research community.com/lianghanfang/UnLiDAR-UAV-Est.
  arXiv  Detail & Related papers  (2024-12-17T09:30:31Z)
• SFTrack: A Robust Scale and Motion Adaptive Algorithm for Tracking Small and Fast Moving Objects [2.9803250365852443]
  This paper addresses the problem of multi-object tracking in Unmanned Aerial Vehicle (UAV) footage. It plays a critical role in various UAV applications, including traffic monitoring systems and real-time suspect tracking by the police. We propose a new tracking strategy, which initiates the tracking of target objects from low-confidence detections.
  arXiv  Detail & Related papers  (2024-10-26T05:09:20Z)
• 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)
• The 3rd Anti-UAV Workshop & Challenge: Methods and Results [65.9405033602133]
  The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UAV Challenge has been publicly released.
  arXiv  Detail & Related papers  (2023-05-12T07:37:04Z)
• Learning to Compress Unmanned Aerial Vehicle (UAV) Captured Video: Benchmark and Analysis [54.07535860237662]
  We propose a novel task for learned UAV video coding and construct a comprehensive and systematic benchmark for such a task. It is expected that the benchmark will accelerate the research and development in video coding on drone platforms.
  arXiv  Detail & Related papers  (2023-01-15T15:18:02Z)
• Vision-Based UAV Self-Positioning in Low-Altitude Urban Environments [20.69412701553767]
  Unmanned Aerial Vehicles (UAVs) rely on satellite systems for stable positioning. In such situations, vision-based techniques can serve as an alternative, ensuring the self-positioning capability of UAVs. This paper presents a new dataset, DenseUAV, which is the first publicly available dataset designed for the UAV self-positioning task.
  arXiv  Detail & Related papers  (2022-01-23T07:18:55Z)
• 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)

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.