mpii-dataset

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"

A PyTorch toolkit for 2D Human Pose Estimation.

Distribution-Aware Coordinate Representation for Human Pose Estimation

Official pytorch Code for CVPR2019 paper "Fast Human Pose Estimation" https://arxiv.org/abs/1811.05419

TensorFlow implementation of "Simple Baselines for Human Pose Estimation and Tracking", ECCV 2018

Official TensorFlow implementation of "PoseFix: Model-agnostic General Human Pose Refinement Network", CVPR 2019

DeepPose implementation on TensorFlow. Original Paper http://arxiv.org/abs/1312.4659

Chainer implementation of Pose Proposal Networks

Simple Baselines for Human Pose Estimation and Tracking

[IJCAI 2022] Code for the paper "Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation"

Evaluation code for the MPII human pose dataset

A fast stacked hourglass network for human pose estimation on OpenVino

Analyzes weightlifting videos for correct posture using pose estimation with OpenCV

2D human pose estimation with DSNT

Pytorch implementation of the paper "Toward fast and accurate human pose estimation via soft-gated skip connections"

Stacked Hourglass Network (shnet) for human pose estimation implemented in PyTorch

This model detects and tracks the pose of the human through Image as well as Video using Computer Vision.

Implementation for Human Pose Estimation using OpenCV

this project is able to detect length of both arms and shoulder to neck distance on a image and video using MPII trained model weights with human pose estimation technique