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Greatest papers with code

FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration

19 Aug 2020facebookresearch/frankmocap

To construct FrankMocap, we build the state-of-the-art monocular 3D "hand" motion capture method by taking the hand part of the whole body parametric model (SMPL-X).

3D HAND POSE ESTIMATION 3D HUMAN RECONSTRUCTION 3D POSE ESTIMATION MOTION CAPTURE

Learning to Estimate 3D Hand Pose from Single RGB Images

ICCV 2017 lmb-freiburg/hand3d

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

3D HAND POSE ESTIMATION SIGN LANGUAGE RECOGNITION

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

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

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

3D HAND POSE ESTIMATION

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

CVPR 2018 mks0601/V2V-PoseNet_RELEASE

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

3D HAND POSE ESTIMATION 3D POSE ESTIMATION

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

CVPR 2018 mks0601/V2V-PoseNet_RELEASE

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.

3D HAND POSE ESTIMATION 3D HUMAN POSE ESTIMATION

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

28 Aug 2017mks0601/V2V-PoseNet_RELEASE

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

3D HAND POSE ESTIMATION DATA AUGMENTATION

Monocular Expressive Body Regression through Body-Driven Attention

ECCV 2020 vchoutas/expose

To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image.

3D FACE RECONSTRUCTION 3D HAND POSE ESTIMATION 3D HUMAN POSE ESTIMATION 3D HUMAN RECONSTRUCTION MOTION CAPTURE

Dense 3D Regression for Hand Pose Estimation

CVPR 2018 melonwan/denseReg

Specifically, we decompose the pose parameters into a set of per-pixel estimations, i. e., 2D heat maps, 3D heat maps and unit 3D directional vector fields.

3D HAND POSE ESTIMATION

First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations

CVPR 2018 guiggh/hand_pose_action

Our dataset and experiments can be of interest to communities of 3D hand pose estimation, 6D object pose, and robotics as well as action recognition.

3D HAND POSE ESTIMATION ACTION RECOGNITION EGOCENTRIC ACTIVITY RECOGNITION HAND GESTURE RECOGNITION