Popular GitHub Repositories for Captured Gestures

A full-body keyboard using gestures to type through computer vision

HAnd Gesture Recognition Image Dataset

A sign language interpreter using live video feed from the camera.

A dataset for estimation of hand pose and shape from single color images.

Major Project - Sign Language To Text Conversion Using Python, Computer Vision and Machine Learning

Awesome Gesture Generation

[ACM MM 2018 Oral] GestureGAN for Hand Gesture-to-Gesture Translation in the Wild

Use Python, OpenCV, and MediaPipe to control a keyboard with facial gestures

The official implementation for ICMI 2020 Best Paper Award "Gesticulator: A framework for semantically-aware speech-driven gesture generation"

A Real Time Object Detection application on iOS using Tensorflow and pre-trained COCO dataset models. Video frames are captured and inference is done locally using the provided mobilenet models. Both Swift and Objective-C projects.

Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application

Slovo: Russian Sign Language Dataset and Models

A Transfer Learning based Object Detection API that detects all objects in an image, video or live webcam. An SSD model and a Faster R-CNN model was pretrained on Mobile net coco dataset along with a label map in Tensorflow. This model were used to detect objects captured in an image, video or real time webcam. Open CV was used for streaming objects and preprocessing.

This is a hand gesture recognition program that replaces the entire MediaPipe process with ONNX. Simultaneous detection of multiple palms and a simple tracker are additionally implemented. In addition, a simple MLP can learn and recognize gestures.

Reference github repository for the paper "Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data". We propose a procedure to generate realistic DP data synthetically. Our synthesis approach mimics the optical image formation found on DP sensors and can be applied to virtual scenes rendered with standard computer software. Leveraging these realistic synthetic DP images, we introduce a new recurrent convolutional network (RCN) architecture that can improve defocus deblurring results and is suitable for use with single-frame and multi-frame data captured by DP sensors.

Reference github repository for the paper "Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning". We propose a single-image deblurring network that incorporates the two sub-aperture views into a multitask framework. Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network’s ability to learn to deblur the image. Our experiments show this multi-task strategy achieves +1dB PSNR improvement over state-of-the-art defocus deblurring methods. In addition, our multi-task framework allows accurate DP-view synthesis (e.g., ~ 39dB PSNR) from the single input image. These high-quality DP views can be used for other DP-based applications, such as reflection removal. As part of this effort, we have captured a new dataset of 7,059 high-quali

A virtual drawing tool that allows you to draw in the air using hand gestures, thanks to the powerful combination of OpenCV and MediaPipe.

A tool to navigate the desktop with hand gestures. Builds on mediapipe.

Face recognition-based attendance system is a process of recognizing the faces of the students while taking attendance by using face bio-metrics based on high – definition monitor video and other information technology. In this face recognition project, a computer system will be able to find and recognize human faces quickly and precisely in images or videos that are being captured through a webcam / a surveillance camera.

An end-to-end system that performs temporal recognition of gesture sequences using speech and skeletal input. The model combines three networks with a CTC output layer that recognises gestures from continuous stream.