Hand Pose Estimation

68 papers with code • 10 benchmarks • 20 datasets

Hand pose estimation is the task of finding the joints of the hand from an image or set of video frames.

( Image credit: Pose-REN )

Libraries

Use these libraries to find Hand Pose Estimation models and implementations
3 papers
2,724

Most implemented papers

Learning from Simulated and Unsupervised Images through Adversarial Training

carpedm20/simulated-unsupervised-tensorflow CVPR 2017

With recent progress in graphics, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations.

Learning to Estimate 3D Hand Pose from Single RGB Images

lmb-freiburg/hand3d ICCV 2017

Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images.

V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map

mks0601/V2V-PoseNet_RELEASE CVPR 2018

To overcome these weaknesses, we firstly cast the 3D hand and human pose estimation problem from a single depth map into a voxel-to-voxel prediction that uses a 3D voxelized grid and estimates the per-voxel likelihood for each keypoint.

DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation

moberweger/deep-prior-pp 28 Aug 2017

DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations of a hand given a depth map.

HOnnotate: A method for 3D Annotation of Hand and Object Poses

shreyashampali/ho3d CVPR 2020

This dataset is currently made of 77, 558 frames, 68 sequences, 10 persons, and 10 objects.

Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals

mks0601/V2V-PoseNet_RELEASE CVPR 2018

Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018

Learning Pose Specific Representations by Predicting Different Views

poier/PreView CVPR 2018

To exploit this observation, we train a model that -- given input from one view -- estimates a latent representation, which is trained to be predictive for the appearance of the object when captured from another viewpoint.

End-to-end Hand Mesh Recovery from a Monocular RGB Image

MandyMo/HAMR ICCV 2019

In this paper, we present a HAnd Mesh Recovery (HAMR) framework to tackle the problem of reconstructing the full 3D mesh of a human hand from a single RGB image.

3D Hand Shape and Pose Estimation from a Single RGB Image

3d-hand-shape/hand-graph-cnn CVPR 2019

This work addresses a novel and challenging problem of estimating the full 3D hand shape and pose from a single RGB image.

A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image

zhangboshen/A2J ICCV 2019

For 3D hand and body pose estimation task in depth image, a novel anchor-based approach termed Anchor-to-Joint regression network (A2J) with the end-to-end learning ability is proposed.