Popular GitHub Repositories for Hand Gesture

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

OpenMMLab Pose Estimation Toolbox and Benchmark.

Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

Awesome work on hand pose estimation/tracking

A library for prototyping realtime hand detection (bounding box), directly in the browser.

Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition

TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.

TransmogrifAI (pronounced tr?ns-m?g?r?-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

pytorch implementation of openpose including Hand and Body Pose Estimation.

The collection of pre-trained, state-of-the-art AI models for ailia SDK

在 oxford hand 数据集上对 YOLOv3 做模型剪枝（network slimming）

Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow

A toolbox for skeleton-based action recognition.

Gesture recognition via CNN. Implemented in Keras + Tensorflow/Theano + OpenCV

ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ? support visual intelligence development!

We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the

Network estimating 3D Handpose from single color images

This is a library that provides dual dexterous hand manipulation tasks through Isaac Gym