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source code for Finding Action Tubes, CVPR 2015
Activity Recognition using Temporal Optical Flow Convolutional Features and Multi-Layer LSTM
Action Recognition Toolbox for CUHKÐZ&SIAT submission to ActivityNet 2016
Real-World Anomaly Detection in Surveillance Videos
Efficient Violence Detection Using 3D Convolutional Neural Networks
Collections for Violence Detection
This is an official implementation of our CVPR 2020 paper "Non-Local Neural Networks With Grouped Bilinear Attentional Transforms".
TensorFlow code and pre-trained models for BERT
BiConvLSTM for violence detection in videos
This Pytorch repo uses BiConvLSTM in a Spatiotemporal Encoder to detect violence in Videos. Three benchmark datasets namely Hockey, Movies and Violent Flows were used in this work.
Action Recognition in Video Sequences using Deep Bi-directional LSTM with CNN Features
C3D is a modified version of BVLC caffe to support 3D ConvNets.
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 reduce the false alarm rate. This paper proposes a novel architecture of ConvLSTM model that can run on low-cost Internet of Things (IOT) device such as raspberry pi board. The paper utilized convolutional neural networks (CNNs) to learn spatial features from video’s frames that were applied to Long Short- Term Memory (LSTM) for video classification into violence/non-violence classes. A complex dataset including two public datasets: RWF-2000 and RLVS-2000 was used for model training and evaluation. The challenging video content includes crowds and chaos, small object at far distance, low resolution, and transient action. Additionally, the videos were captured in various environments such as street, prison, and schools with several human actions such as playing football, basketball, tennis, swimming and eating. The experimental results show high performance of the proposed violence detection model in terms of average metrics having an accuracy of 73.35 %, recall of 76.90 %, precision of 72.53 %, F1 score of 74.01 %, false negative rate of 23.10 %, false positive rate of 30.20 %, and AUC of 82.0 %.
menovideo: pytorch library for video action recognition and video understanding
Implementation of the model ( Violence Detection) using CNN+ LSTM and tensorflow and keras as backend )
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Dynamic Image Networks for Action Recognition
New generated dataset for fight detection in surveillance cameras.
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
a HR-based multi-stream CNN descriptor (HR-MSCNN) is formulated to recognize human action
Code for the paper "Human Activity Analysis: Iterative Weak/Self-Supervised Learning Frameworks for Detecting Abnormal Events", IJCB 2020
A human violence detection & classification system using recurrent neural networks(RNN).
Convolutional neural network model for video classification trained on the Kinetics dataset.
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Colar: Effective and Efficient Online Action Detection by Consulting Exemplars, CVPR 2022.
A skeleton-based real-time online action recognition project, classifying and recognizing base on framewise joints, which can be used for safety surveilence.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.