338 Open source projects that are alternatives of or similar to Human Falling Detect Tracks

Ordinare sorts gems in your Gemfile alphabetically

Android video listing with swipe view tabs based on mvp design pattern with complete functionalities like search and sort

Package providing helper functions for a Laravel REST-API

Full Phoenix Support for Rummage. It can be used for searching, sorting and paginating collections in phoenix.

Epipolar Transformers (CVPR 2020)

VPoser: Variational Human Pose Prior

[ICCV 2019] Official implementation of "MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation" in PyTorch + Social Distancing

a toolkit for pose estimation using deep learning

A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.

A simple baseline for 3d human pose estimation in PyTorch.

Implement of Openpose use Tensorflow

tf-openpose Based iOS Project

Perception toolkit for sim2real training and validation

Code repository for the paper: "Coherent Reconstruction of Multiple Humans from a Single Image" in CVPR'20

face keypoints deteciton based on stackedhourglass

Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation

Perform Human Pose Estimation in OpenCV Using OpenPose MobileNet

⚾🤖⚾ Automatic baseball pitching overlay in realtime

We present MocapNET2, 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 (70 fps in CPU-only execution).

pytorch implementation of MultiPoseNet (ECCV 2018, Muhammed Kocabas et al.)

Code for paper "A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image". ICCV2019

Source code of CVPR 2020 paper, "HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation"

This work is used for pose estimation(yaw, pitch and roll) by Face landmarks(left eye, right eye, nose, left mouth, right mouth and chin)

This is a pix2pix demo that learns from pose and translates this into a human. A webcam-enabled application is also provided that translates your pose to the trained pose. Everybody dance now !

Data preparation and loader for AMASS

Implementation of ICRA 2019 paper: Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation

3D hand pose estimation via dense regression

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

API for the dataset proposed in "Pose2Seg: Detection Free Human Instance Segmentation" @ CVPR2019.

A python program to detect and classify hand pose using deep learning techniques

Activity Recognition from 2D pose using an LSTM RNN

💎 "Marker-less Augmented Reality" with OpenCV and OpenGL.

LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.

A collection of awesome resources in Human Pose estimation.

SynthDet - An end-to-end object detection pipeline using synthetic data

Odin: Pose estimation-based tracking and counting of people in videos

I checked the performance by running PoseNet on CoreML

Fast and accurate single-person pose estimation, ranked 10th at CVPR'19 LIP challenge. Contains implementation of "Global Context for Convolutional Pose Machines" paper.