Using a Stereo-Vision Setup to reliably track a Player's Elbow

Reference ImageNet implementation of SelecSLS CNN architecture proposed in "XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera". Also includes code for pruning the model based on implicit sparsity emerging from adaptive gradient descent methods.

Multiperson Human Pose Estimation on a video in 3D

This repository provides a solution for estimating 3D positions using feature-based detection and deep learning model integrated with OpenCV's Deep Neural Network (DNN) and the Robot Operating System (ROS).

Undergraduate Internship 학부인턴십 활동 (July 2022~)

Pytorch implementation of 3D human keypoints estimation models

New egocentric synthetic dataset for egocentric 3D human pose estimation

Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"

A simple baseline for 3d human pose estimation in tensorflow v2.

Modular Robotics | Computer Vision 2D | Object Detection | 3D Pose Estimation

Real-time 3D multi-person pose estimation demo in PyTorch. OpenVINO backend can be used for fast inference on CPU.

A simple yet effective method for 3D pose estimation using only 2D supervison

Exploring the use of Adversarial Constrained Autoencoder Interpolation (ACAI) to improve the quality of latent space for 3D human pose representation using the h36m dataset.

PerfectRep is a 3D pose estimation model tailored specifically for powerlifting analysis. It allows for precise tracking and analysis of lifter's movements to ensure perfect form and technique.

Pytorch implementation for the paper: "DAGM-Mono: Deformable Attention-Guided Modeling for Monocular 3D Reconstruction"

3D pose estimation of mushrooms from pointcloud - trained on synthetic data

This is a for of the original implementation, sharing so that anyone interested in using it on windows without a gpu in the system can run it

3D OpenPose using ROS. Includes Hand and Face Detection extensions as well.

Code for course project `Machine Perception` at ETH Zurich, Spring 2019.