Keras implementation of Human Action Recognition for the data set State Farm Distracted Driver Detection (Kaggle)
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Updated
Sep 23, 2016 - Python
Keras implementation of Human Action Recognition for the data set State Farm Distracted Driver Detection (Kaggle)
A system for Human Action Recognition that uses the scale and body orientation invariant Skeletal Quads representation, with an LSTM network
A human action dataset collected from Elder Scrolls V: Skyrim
Deep learning model that predicts human action in a given video feed using pose estimation
Human Activity Recognition UCI Dataset, final score 0.97196
A skeleton-based real-time online action recognition project, classifying and recognizing base on framewise joints, which can be used for safety surveilence.
MSR Action Recognition Datasets and Codes
Computer Vision Project : Action Recognition on UCF101 Dataset
This python opencv code is used to segment the human object from the video frame
A Comprehensive Tutorial on Video Modeling
Source code for "Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching", AAAI2020
Project to explore a deep learning solution to a computer vision problem. Human action recognition has become increasingly popular. This project implements a deep RNN to detect seizures.
Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all cropped spatio-temporally and filmed from a surveillance-camera like position.
Synthetically Generated Surveillance Perspective Human Action Recognition Dataset: 6901 Videos from 10 action classes, made by a 3D Simulation, all cropped spatio-temporally and filmed from a surveillance-camera like position.
This is an effort to provide different approaches towards human action recognition from video. A method to perform data augmentation on skeletal data so as to achieve a view independent recognition approach is included.
Activity Recognition using Temporal Optical Flow Convolutional Features and Multi-Layer LSTM
Implementation of CNN-Based Model for Online Action Recognition
This includes a novel method to measure the quality of the actions performed in Olympic weightlifting using human action recognition in videos. Human action recognition is a well-studied problem in computer vision and on the other hand action quality assessment is researched and experimented comparatively low. This is due to the lack of datasets…
his is a human action recognition(HAR) project based on CNNs and Tensorflow using a pretrained model.
Implementation of some popular skeleton based Human Action Recognition methods basis on Deep Neural Networks.
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