# Automatic Handgun Detection Alarm in Videos Using Deep Learning

arXiv: https://arxiv.org/abs/1702.05147 · HTML: https://mlsanity.com/paper/1702.05147/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Feb 2017.

## Built on by (most cited first, 15 of 15)

- [T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition](https://mlsanity.com/paper/2409.19734/) (2024)
- [HOD: A Benchmark Dataset for Harmful Object Detection](https://mlsanity.com/paper/2310.05192/) (2023)
- [A Dataset and System for Real-Time Gun Detection in Surveillance Video Using Deep Learning](https://mlsanity.com/paper/2105.01058/) (2021)
- [TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video](https://mlsanity.com/paper/2111.08867/) (2021)
- [YouTube-GDD: A challenging gun detection dataset with rich contextual information](https://mlsanity.com/paper/2203.04129/) (2022)
- [Real Time Deep Learning Weapon Detection Techniques for Mitigating Lone Wolf Attacks](https://mlsanity.com/paper/2405.14148/) (2024)
- [Accurate and Efficient Two-Stage Gun Detection in Video](https://mlsanity.com/paper/2503.06317/) (2025)
- [Gun Detection Using Combined Human Pose and Weapon Appearance](https://mlsanity.com/paper/2503.12215/) (2025)
- [MULTICAST: MULTI Confirmation-level Alarm SysTem based on CNN and LSTM to mitigate false alarms for handgun detection in video-surveillance](https://mlsanity.com/paper/2104.11653/) (2021)
- [A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training](https://mlsanity.com/paper/2109.03748/) (2021)
- [Orientation Aware Weapons Detection In Visual Data : A Benchmark Dataset](https://mlsanity.com/paper/2112.02221/) (2021)
- [CCTV-Gun: Benchmarking Handgun Detection in CCTV Images](https://mlsanity.com/paper/2303.10703/) (2023)
- [Detection and Localization of Firearm Carriers in Complex Scenes for Improved Safety Measures](https://mlsanity.com/paper/2309.09236/) (2023)
- [Transfer Learning-based Real-time Handgun Detection](https://mlsanity.com/paper/2311.13559/) (2023)
- [Optimizing Convolutional Neural Network Architecture](https://mlsanity.com/paper/2401.01361/) (2023)

## Abstract (arXiv)

Current surveillance and control systems still require human supervision and intervention. This work presents a novel automatic handgun detection system in videos appropriate for both, surveillance and control purposes. We reformulate this detection problem into the problem of minimizing false positives and solve it by building the key training data-set guided by the results of a deep Convolutional Neural Networks (CNN) classifier, then assessing the best classification model under two approaches, the sliding window approach and region proposal approach. The most promising results are obtained by Faster R-CNN based model trained on our new database. The best detector show a high potential even in low quality youtube videos and provides satisfactory results as automatic alarm system. Among 30 scenes, it successfully activates the alarm after five successive true positives in less than 0.2 seconds, in 27 scenes. We also define a new metric, Alarm Activation per Interval (AApI), to assess the performance of a detection model as an automatic detection system in videos.