human-pose-estimation topic
keras_Realtime_Multi-Person_Pose_Estimation
Keras version of Realtime Multi-Person Pose Estimation project
ICON
[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals
kapao
KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
EpipolarPose
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry (CVPR2019)
3DMPPE_POSENET_RELEASE
Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019
3DMPPE_ROOTNET_RELEASE
Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019
PoseFix_RELEASE
Official TensorFlow implementation of "PoseFix: Model-agnostic General Human Pose Refinement Network", CVPR 2019
TF-SimpleHumanPose
TensorFlow implementation of "Simple Baselines for Human Pose Estimation and Tracking", ECCV 2018
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
deep-high-resolution-net.pytorch
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"