UAV Detection

UAV: Unmanned Aerial Vehicle

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25 papers1 paper in the last four weeks, down 75% on the four weeks before. 0.0% of all new papers.

What Frame-Level Labels Can and Cannot Do for Small-UAV Point Detection in Thermal Video
Oct 6, 2026Wonbin Son, Gyumum Choi, Junil Seo +1Infrared Small Target Detection UAV Detection
HDMamba-YOLO: Efficient State-Space Perception and Local Spatial Reconstruction for UAV Small Object
Sep 19, 2026Linduo Wei, Junjie Fan, Yijun Mai +1Aerial Object Detection Remote Sensing Small Object Detection
School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094, China · School of Intellectual Property, Nanjing University of Science and Technology, Nanjing, 210094, China · School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
Project SCOUT: Interceptor Drone for Perimeter Defense
Sep 17, 2026Azmain Yousuf, Siwei Cai, Knut Peterson +2Aerial Robotics Visual Object Tracking
Drexel University
Evaluating the Robustness of Anti-UAV Detection under Controlled Fog Degradation: Fog-Aware Training and Clear-Sky Tradeoff
Sep 10, 2026Gur Levy Birkental, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor AlsahagUAV Detection Object Detection
University of Amsterdam Amsterdam, The Netherlands · Department of Computer Science and Technology, SUNY Empire State University Saratoga Springs, NY, USA
Evidential Deep Learning for Multi-Modal Anti-UAV Detection
Sep 1, 2026Dmitry Golovchits, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor AlsahagEvidential Deep Learning Dempster-Shafer Theory
University of Amsterdam Amsterdam, The Netherlands
Human-in-the-Loop Signature Bootstrapping for UAV Hyperspectral PFM-1 Mine Detection
Jul 28, 2026Sagar Lekhak, Prasanna Reddy Pulakurthi, Emmett J. IentilucciHuman-in-the-Loop Annotation Hyperspectral Imaging
Rochester Institute of Technology, Rochester, NY 14623, USA
Gaze-DETR: Top-Down Guidance Through Priority Maps for Infrared Weak-Small UAV Detection with DETR
Jul 21, 2026Nian Liu, Yuxin Yang, Shubo Lin +6Infrared Small Target Detection Detection Transformer
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China · School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences, Beijing 101408, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China +3
SkyEV: RGB-Event UAV detection and tracking dataset and baseline
Jul 21, 2026Jakub Mandula, Sebastian Heusinger, Julian Moosmann +2Visual Object Tracking Small Object Detection
ETH Zurich
ASUMOT: Motion-Consistency-Based Asynchronous UAV Detection and Tracking with Event Cameras
Jul 13, 2026Baofeng Jia, Xiaoyu Chen, Jingyuan Zhang +4Event-Based Vision Event-Based Object Detection
State key Laboratory of Extreme Environment Optoelectronic Dynamic Testing Technology and Instrument, Nanjing University of Science and Technology, Nanjing 210094, China · Jiangsu Key Laboratory of Visual Sensing and Intelligent Perception, Nanjing University of Science and Technology, Nanjing 210094, China
EchoHawk: A Reproducible Acoustic Pipeline for Drone Detection, Classification, and Direction-Finding, with a Cautionary Study of Session-Level Data Leakage
Jun 28, 2026David ShulmanData Leakage Direction-of-Arrival Estimation
DroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace
Jun 10, 2026Marius BayizereGraph Neural Networks UAV Detection
Independent Researcher, Kigali, Rwanda
EventRadar: Long-Range Visual UAV Discovery through Spatiotemporal Event Sensing
Jun 9, 2026Zhiting Zhou, Xingchen Liu, Xinglin Yu +5Event-Based Vision UAV Detection
Shenzhen International Graduate School, Tsinghua University · Sun Yat-sen University · Harbin Institute of Technology, Shenzhen +3
Classification and detection of multiple UAVs using rational Gaussian wavelet neural networks
May 25, 2026Ungvári Gergő, Ferenc Braun, Attila Ámon +4Wavelet Methods Aerial Object Detection
Department of Numerical Analysis, Eötvös Loránd University, Pázmány Péter sétány, Budapest, 1117, Hungary. · System and Control Laboratory, HUN-REN Institute for Computer Science and Control, Kende utca, Budapest, 1111, Hungary. · HUN-REN Centre for Energy Research, Konkoly-Thege Miklós út, Budapest, 1121, Hungary. +3
Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection
May 21, 2026Liuyang Wang, Feitian ZhangVideo Object Detection Object Detection
Robotics and Control Laboratory, Department of Robotics, School of Advanced Manufacturing and Robotics, and the State Key Laboratory of Turbulence and Complex Systems, Peking University, Beijing, 100871, China · Great Bay University, Guangdong 523808, China
Towards UAV Detection in the Real World: A New Multispectral Dataset UAVNet-MS and a New Method
May 20, 2026Yihang Luo, Jun Chen, Chao Xiao +13Multispectral Object Detection Small Object Detection
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China · Aviation University of Air Force, China · Sun Yat-sen University, China
LER-YOLO: Reliability-Aware Expert Routing for Misaligned RGB-Infrared UAV Detection
May 20, 2026Liming Hou, Yueping Peng, Hexiang Hao +6Infrared Object Detection Multispectral Object Detection
Engineering University of PAP, Xi’an 710086, China · Unit Command Department, Officers College of PAP, Chengdu 610213, China
XAI and Statistical Analysis for Reliable Intrusion Detection in the UAVIDS-2025 Dataset: From Tree to Hybrid and Tabular DNN Ensembles
May 13, 2026Iakovos-Christos Zarkadis, Christos DouligerisEnsemble Learning Network Intrusion Detection
University of Piraeus Athens, Greece · Dept. of Informatics University of Piraeus Piraeus, Greece
M $^2$ E-UAV: A Benchmark and Analysis for Onboard Motion-on-Motion Event-Based Tiny UAV Detection
May 11, 2026Weiqi Yan, Lixin Chen, Xiangrui Hou +5Small Object Detection Event-Based Object Detection
Fujian Key Laboratory of Urban Intelligent Sensing and Computing, School of Informatics, Xiamen University, Xiamen, China · Meta, Menlo Park, USA
Optimizing Data Augmentation for Real-Time Small UAV Detection: A Lightweight Context-Aware Approach
Apr 21, 2026Amir Zamani, Zeinab AbediniData Augmentation Small Object Detection
Department of Computer Engineering, Comprehensive University of the Islamic Revolution, Tehran, Iran · Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
HEP Statistical Inference for UAV Fault Detection: CLs, LRT, and SBI Applied to Blade Damage
Mar 19, 2026KhushiyantLikelihood Ratio Testing Fault Detection
Department of Computer Science, University of Freiburg
Unsupervised LiDAR-Based Multi-UAV Detection and Tracking Under Extreme Sparsity
Mar 12, 2026Nivand Khosravi, Rodrigo Ventura, Meysam BasiriUAV Detection Aerial Object Detection
Instituto Superior T´ecnico, University of Lisbon, Lisbon, Portugal
Real-Time Drone Detection in Event Cameras via Per-Pixel Frequency Analysis
Mar 9, 2026Michael Bezick, Majid SahinUAV Detection Aerial Object Detection
Johns Hopkins University APL
Alignment-Aware and Reliability-Gated Multimodal Fusion for Unmanned Aerial Vehicle Detection Across Heterogeneous Thermal-Visual Sensors
Mar 9, 2026Ishrat Jahan, Molla E Majid, M Murugappan +5UAV Detection Multimodal Sensor Fusion
Department of Computer Science and Engineering, Shahjalal University of Science & Technology, Sylhet, Bangladesh · Computer Applications Department, Academic Bridge Program, Qatar Foundation, Doha, Qatar. · Intelligent Signal Processing (ISP) Research Lab, Department of Electronics and Communication Engineering, Kuwait College of Science and Technology, Block 4, Doha, Kuwait +5
ODD-SEC: Onboard Drone Detection with a Spinning Event Camera
Mar 6, 2026Kuan Dai, Hongxin Zhang, Sheng Zhong +1UAV Detection Aerial Object Detection
Neuromorphic Automation and Intelligence Lab (NAIL) at School of Artificial Intelligence and Robotics, Hunan University, Changsha, China.
CollabOD: Collaborative Multi-Backbone with Cross-scale Vision for UAV Small Object Detection
Mar 6, 2026Xuecheng Bai, Yuxiang Wang, Chuanzhi Xu +3Efficient Object Detection Small Object Detection
Aviation Traffic Control Technology (SHENZHEN) Co., Ltd., Shenzhen, China · The University of Sydney, NSW, Australia · Research Institute of Traffic Control Technology Co., Ltd., Beijing, China +1

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What Frame-Level Labels Can and Cannot Do for Small-UAV Point Detection in Thermal Video

Wonbin Son, Gyumum Choi, Junil Seo, Hyungjoon Kim

Infrared Small Target Detection UAV Detection Weakly Supervised Learning Aerial Object Detection

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The growing use of unmanned aerial vehicles (UAVs) has increased the importance of image-based UAV detection. Learning-based detectors are trained on imagery and annotations, with annotation type determining the information available during training. We focus on learning localization from frame-level target presence/absence labels when sensor or scene changes make spatial annotations for additional training burdensome. We analyze the detection capability, learning behavior, and potential applications of an existing architecture for point detection of small UAVs, trained with presence/absence labels and requiring no external detector. The architecture freezes spatial features learned through classification and trains a readout with the same frame labels to produce spatial score maps and point detections. On two thermal infrared datasets, CST Anti-UAV and Anti-UAV410, we evaluate localization hit rates and detection rates under false-alarm constraints, analyze the effects of training stages, label allocation, synthesis, and model configuration, and compare with bounding-box detectors. We also explore potential applications on Airborne Object Tracking (AOT) using its visible-light imagery and frame labels. Classification training strengthened target-related spatial responses, while readout training helped extract them consistently. Distributing similar label counts across more videos yielded higher localization hit rates, while synthesis effects varied by dataset and evaluation criterion. Higher localization hit rates did not always improve detection under false-alarm constraints, and failures remained when target signals were weak relative to background variation and under cross-dataset transfer. These findings provide guidance on label allocation, spatial representations and readouts, synthesis, and false-alarm control.