Deep learning based content moderation from text, audio, video & image input modalities.

Violence Detection using 3D Convolutional Neural Networks

Surveillance System Against Violence

Deep learning based algorithm which is capable of detecting violence in indoor or outdoor environments: fight, fire or car crash and even more

A human violence detection & classification system using recurrent neural networks(RNN).

Efficient violence detection in surveillance videos using Human Skeletons and Motion Estimation

Realtime Violence Detection with Raspberry-pi

빅데이터 연합동아리 BOAZ 12기 ADV Vision 팀 [Fight Detection] 레포지토리입니다.

real-time violence detection on video content

Abstract— Violence detection has been investigated extensively in the literature. Recently, IOT based violence video surveillance is an intelligent component integrated in security system of smart buildings. Violence video detector is a specific kind of detection models that should be highly accurate to increase the model’s sensitivity and reduc…

This project aims at classifying a video into a fight or non-fight video

I3D implemetation in Keras + video preprocessing (rgb and optical flows) to detect violence in videos with weak labels (Weakly Supervised) on XD-Violence dataset (Multi-Label, Multi-class and untrimmed videos) using Keras

Deeply Supervised Practical Implementation of Violence Detection from Videos for Maximizing Performance

Explainable Content Moderation performed using CNNs and visualized using Grad-CAM

Two neural networks to detect weapons and violence in videos

This project focuses on the comparative analysis of machine learning models for the task of violence detection in images or videos. Violence detection is a crucial application with various real-world use cases, including surveillance, content moderation, and public safety.