openpose VS PoseAngleEstimation

Compare openpose vs PoseAngleEstimation and see what are their differences.

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openpose PoseAngleEstimation
36 1
29,627 24
1.4% -
5.2 2.5
12 days ago 6 months ago
C++ Python
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

openpose

Posts with mentions or reviews of openpose. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-25.

PoseAngleEstimation

Posts with mentions or reviews of PoseAngleEstimation. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-12.

What are some alternatives?

When comparing openpose and PoseAngleEstimation you can also consider the following projects:

mediapipe - Cross-platform, customizable ML solutions for live and streaming media.

AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.

lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.

BlazePose-tensorflow - A third-party Tensorflow Implementation for paper "BlazePose: On-device Real-time Body Pose tracking".

MocapNET - We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance

freemocap - Free Motion Capture for Everyone 💀✨

jetson-inference - Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

VIBE - Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"

Caffe - Caffe: a fast open framework for deep learning.

tfjs-models - Pretrained models for TensorFlow.js