85 Open source projects that are alternatives of or similar to Human Pose Estimation.pytorch

🌌 OpenVTuber-虚拟アイドル共享计划 An application of real-time face and gaze analyzation via deep nerual networks.

Using DenseNet for human pose estimation based on TensorFlow.

A fast stacked hourglass network for human pose estimation on OpenVino

ICON: Implicit Clothed humans Obtained from Normals (CVPR 2022)

Code for ICCV2021 paper PARE: Part Attention Regressor for 3D Human Body Estimation

Evaluation code for the MPII human pose dataset

Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose Estimation

Official implementation of ACCV 2020 paper "3D Human Motion Estimation via Motion Compression and Refinement" (Identical repo to https://github.com/KlabCMU/MEVA, will be kept in sync)

[ICCV '21] In this repository you find the code to our paper "Keypoint Communities".

This is the proposal network for MultiPerson Pose Estimation.

KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.

pytorch realtime multi person keypoint estimation

OpenPose wrapper written in C++ and C# for Windows

Posture recognition based on common camera

Pytorch version reinplement code of PyraNet , for paper : Learning Feature Pyramids for Human Pose Estimation

This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.

Code for our ICCV 19 paper : Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking

BlazePoseBarracuda is a human 2D/3D pose estimation neural network that runs the Mediapipe Pose (BlazePose) pipeline on the Unity Barracuda with GPU.

This demo uses a deep neural network and two generic cameras to perform 3D pose estimation.

[ICCV 2019] Official implementation of "MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation" in PyTorch + Social Distancing

Human 3.6M 3D human pose dataset fetcher

Code for "Learning Feature Pyramids for Human Pose Estimation" (ICCV 2017)

Code for "Quantized Densely Connected U-Nets for Efficient Landmark Localization" (ECCV 2018) and "CU-Net: Coupled U-Nets" (BMVC 2018 oral)

This code implements a demo of the Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources paper by Adrian Bulat and Georgios Tzimiropoulos.

Pytorch version of Realtime Multi-Person Pose Estimation project