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Found 6 papers, 1 papers with code
Implicit Learning of Scene Geometry from Poses for Global Localization
In this paper, we propose to utilize these minimal available labels (. i. e, poses) to learn the underlying 3D geometry of the scene and use the geometry to estimate the 6 DoF camera pose.
Global Localization: Utilizing Relative Spatio-Temporal Geometric Constraints from Adjacent and Distant Cameras
In this work, we address the problem of estimating the 6 DoF camera pose relative to a global frame from a single image.
Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.
Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer
In addition to the pose estimation task, the voting-based scheme can also provide point cloud segmentation result without ground-truth for segmentation.
Model-based Hand Pose Estimation for Generalized Hand Shape with Appearance Normalization
In this work, we extend the kinematic layer to make the hand shape parameters learnable.
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
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
Ranked #5 on
Hand Pose Estimation
on HANDS 2017
