# RWF-2000: An Open Large Scale Video Database for Violence Detection

arXiv: https://arxiv.org/abs/1911.05913 · HTML: https://mlsanity.com/paper/1911.05913/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Nov 2019.

## Built on by (most cited first, 30 of 39)

- [Deep Learning for Video Anomaly Detection: A Review](https://mlsanity.com/paper/2409.05383/) (2024)
- [Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Features](https://mlsanity.com/paper/2303.15167/) (2023)
- [Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling](https://mlsanity.com/paper/2303.15270/) (2023)
- [Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition](https://mlsanity.com/paper/2306.11546/) (2023)
- [Skeletal Video Anomaly Detection using Deep Learning: Survey, Challenges and Future Directions](https://mlsanity.com/paper/2301.00114/) (2022)
- [DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios](https://mlsanity.com/paper/2506.05372/) (2025)
- [Efficient Two-Stream Network for Violence Detection Using Separable Convolutional LSTM](https://mlsanity.com/paper/2102.10590/) (2021)
- [Sherlock: Towards Multi-scene Video Abnormal Event Extraction and Localization via a Global-local Spatial-sensitive LLM](https://mlsanity.com/paper/2502.18863/) (2025)
- [CUE-Net: Violence Detection Video Analytics with Spatial Cropping, Enhanced UniformerV2 and Modified Efficient Additive Attention](https://mlsanity.com/paper/2404.18952/) (2024)
- [Language-guided Open-world Video Anomaly Detection under Weak Supervision](https://mlsanity.com/paper/2503.13160/) (2025)
- [Video Violence Recognition and Localization Using a Semi-Supervised Hard Attention Model](https://mlsanity.com/paper/2202.02212/) (2022)
- [Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection](https://mlsanity.com/paper/2412.03044/) (2024)
- [Weakly Supervised Two-Stage Training Scheme for Deep Video Fight Detection Model](https://mlsanity.com/paper/2209.11477/) (2022)
- [An Overview of Violence Detection Techniques: Current Challenges and Future Directions](https://mlsanity.com/paper/2209.11680/) (2022)
- [Evaluation of Vision-LLMs in Surveillance Video](https://mlsanity.com/paper/2510.23190/) (2025)
- [A Multi-Task Deep Learning Framework for Real-Time Intelligent Video Surveillance with Temporal Event Validation](https://mlsanity.com/paper/2607.03131/) (2026)
- [Multimedia Datasets for Anomaly Detection: A Review](https://mlsanity.com/paper/2112.05410/) (2021)
- [SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized Violence](https://mlsanity.com/paper/2207.12850/) (2022)
- [Balancing Accuracy and Training Time in Federated Learning for Violence Detection in Surveillance Videos: A Study of Neural Network Architectures](https://mlsanity.com/paper/2308.05106/) (2023)
- [JOSENet: A Joint Stream Embedding Network for Violence Detection in Surveillance Videos](https://mlsanity.com/paper/2405.02961/) (2024)
- [Improving Video Violence Recognition with Human Interaction Learning on 3D Skeleton Point Clouds](https://mlsanity.com/paper/2308.13866/) (2023)
- [Two-Stage Violence Detection Using ViTPose and Classification Models at Smart Airports](https://mlsanity.com/paper/2308.16325/) (2023)
- [Reinforcement Learning-based Mixture of Vision Transformers for Video Violence Recognition](https://mlsanity.com/paper/2310.03108/) (2023)
- [Exploring Personalized Federated Learning Architectures for Violence Detection in Surveillance Videos](https://mlsanity.com/paper/2504.00857/) (2025)
- [FuseMamba-VD: Dual Branch VideoMamba with Gated Class Token Fusion for Violence Detection](https://mlsanity.com/paper/2506.03162/) (2025)
- [CompAgent: An Agentic Framework for Visual Compliance Verification](https://mlsanity.com/paper/2511.00171/) (2025)
- [Fight Detection from Still Images in the Wild](https://mlsanity.com/paper/2111.08370/) (2021)
- [Two-stream Multi-dimensional Convolutional Network for Real-time Violence Detection](https://mlsanity.com/paper/2211.04255/) (2022)
- [DIFEM: Key-points Interaction based Feature Extraction Module for Violence Recognition in Videos](https://mlsanity.com/paper/2412.05386/) (2024)
- [Intelligent Image Sensing for Crime Analysis: A ML Approach towards Enhanced Violence Detection and Investigation](https://mlsanity.com/paper/2506.13910/) (2025)

## Abstract (arXiv)

In recent years, surveillance cameras are widely deployed in public places, and the general crime rate has been reduced significantly due to these ubiquitous devices. Usually, these cameras provide cues and evidence after crimes are conducted, while they are rarely used to prevent or stop criminal activities in time. It is both time and labor consuming to manually monitor a large amount of video data from surveillance cameras. Therefore, automatically recognizing violent behaviors from video signals becomes essential. This paper summarizes several existing video datasets for violence detection and proposes the RWF-2000 database with 2,000 videos captured by surveillance cameras in real-world scenes. Also, we present a new method that utilizes both the merits of 3D-CNNs and optical flow, namely Flow Gated Network. The proposed approach obtains an accuracy of 87.25% on the test set of our proposed database. The database and source codes are currently open to access.