Markerless Motion Capture

7 papers with code • 0 benchmarks • 1 datasets

This task has no description! Would you like to contribute one?


Most implemented papers

Capturing and Inferring Dense Full-Body Human-Scene Contact

paulchhuang/bstro CVPR 2022

We capture a new dataset called RICH for "Real scenes, Interaction, Contact and Humans."

Rethinking Pose in 3D: Multi-stage Refinement and Recovery for Markerless Motion Capture

MatteoT90/WibergianLearning 4 Aug 2018

We propose a CNN-based approach for multi-camera markerless motion capture of the human body.

SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos

ChenFengYe/SportsCap 23 Apr 2021

In this paper, we propose SportsCap -- the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input.

A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets

doanduyvo/deeplab_human 7 Jan 2022

Markerless motion capture has become an active field of research in computer vision in recent years.

PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images

HongwenZhang/PyMAF 13 Jul 2022

To address these issues, we propose a Pyramidal Mesh Alignment Feedback (PyMAF) loop in our regression network for well-aligned human mesh recovery and extend it as PyMAF-X for the recovery of expressive full-body models.

Towards Single Camera Human 3D-Kinematics

bittnerma/direct3dkinematicestimation 13 Jan 2023

Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive motion capture labs; however, current approaches are limited by performing multiple de-coupled steps to estimate the kinematics of a person from videos.