There are 1 repository under conv3d topic.
lock mechanism with face recognition and liveness detection
My experimentation around action recognition in videos. Contains Keras implementation for C3D network based on original paper "Learning Spatiotemporal Features with 3D Convolutional Networks", Tran et al. and it includes video processing pipelines coded using mPyPl package. Model is being benchmarked on popular UCF101 dataset and achieves results similar to those reported by authors
Repository processes CT scanned images of human Lungs , which are in DICOM image format. Visualises the data in 3D and trains a 3D convolution network on the data after preprocessing.
An experimental project for autonomous vehicle driving perception with steering angle prediction and semantic segmentation using a combination of UNet, attention and transformers.
Gender classification on 3D IXI Brain MRI dataset with Keras and Tensorflow
A python class compatible with TensorFlow to perform data augmentation on 3D objects during CNN training.
This repository contains my personal code for the paper Learning Spatiotemporal Features with 3D Convolutional Networks by Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri.
Imagine you are working as a data scientist at a home electronics company which manufactures state of the art smart televisions. You want to develop a cool feature in the smart-TV that can recognize five different gestures performed by the user which will help users control the TV without using a remote.
A Simple Three Dimensional Convolutional Neural Networks approach
Data science Mini projects
Hand gesture recognition using convolutional neural network and recurrent neural network
The objective of this project is to recognize hand gestures using state-of-the-art neural networks.
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
Real-Time Visual Speech and Emotion Recognition (ViSpEr) an end-to-end neural network for the low-resource visual speech and facial emotion recognition task, using 3D CNNs and LSTMs
Hand Gesture Recognition using Deep Learning Framework
My team partner and I did this project where we developed a feature in a company’s smart TV that can recognise five different predetermined gestures performed by the user, which will help users control the TV without using a remote.
Develop a conv3D model that can recognise five different gestures performed by the user which will help users control the TV without using a remote
Transform TV control with Gesture Recognition! Enable intuitive interaction with smart TVs using gestures built using Conv3D, CNN & RNN
어린이집 CCTV로 학대상황 감지
Develop a cool feature in the smart-TV that can recognise five different gestures performed by the user which will help users control the TV without using a remote.
Lip reading using TensorFlow, OpenCV, and Keras involves training a deep learning model to recognize spoken words by analyzing lip movements from video frames. The process starts with OpenCV for capturing and preprocessing video frames, focusing on the speaker’s lips. These frames are then fed into a neural network built using Keras and TensorFlow.
Context Understanding from Videos analyzes video content by extracting frames and audio, then detecting objects, faces, emotions, and actions. It uses Python with OpenCV, MoviePy, and YOLO. Future plans include embedding models for improved context analysis.