aric0103

aric0103's Stars

• MVIG-SJTU/AlphaPose

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

  Language:Python8.1k2071.1k2k

• facebookresearch/VideoPose3D

  Efficient 3D human pose estimation in video using 2D keypoint trajectories

  Language:Python3.7k103232757

• mkocabas/VIBE

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

  Language:Python2.9k66265552

• akanazawa/hmr

  Project page for End-to-end Recovery of Human Shape and Pose

  Language:Python1.6k65159391

• ZHOUYI1023/awesome-radar-perception

  A curated list of radar datasets, detection, tracking and fusion

  1.4k685286

• nkolot/SPIN

  Repository for the paper "Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop"

  Language:Python82723132173

• microsoft/multiview-human-pose-estimation-pytorch

  This is an official Pytorch implementation of "Cross View Fusion for 3D Human Pose Estimation, ICCV 2019".

  Language:Python549264889

• zczcwh/PoseFormer

  The project is an official implementation of our paper "3D Human Pose Estimation with Spatial and Temporal Transformers".

  Language:Python49893774

• zczcwh/DL-HPE

  48716140

• sail-sg/mvp

  NeurIPS-2021: Direct Multi-view Multi-person 3D Human Pose Estimation

  Language:Python335113434

• radar-lab/ti_mmwave_rospkg

  TI mmWave radar ROS driver (with sensor fusion and hybrid)

  Language:C++2682044102

• nesl/RadHAR

  Human Activity Recognition from Point Clouds Generated through a Millimeter-wave Radar

  Language:Python163121353

• ivannz/cplxmodule

  Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.

  Language:Python138111927

• ramdrop/autoplace

  Implementation for the paper: AutoPlace: Robust Place Recognition with Single-chip Automotive Radar

  Language:Python1063823

• chstetco/virtualradar

  Open-Source Millimeter-Wave Radar Simulation Framework by Institute of Smart System Technologies, University of Klagenfurt and Institute of Mechatronics and Robotics, JOANNEUM RESEARCH

  Language:C#922922

• MadhavShashi/Human-Activity-Recognition-Using-Smartphones-Sensor-DataSet

  Human activity recognition, is a challenging time series classification task. It involves predicting the movement of a person based on sensor data and traditionally involves deep domain expertise and methods from signal processing to correctly engineer features from the raw data in order to fit a machine learning model.

  Language:Jupyter Notebook711023

• fengxudi/mmWave-gesture-dataset

  694213

• FIGLAB/Vid2Doppler

  This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.

  Language:Python477217