pose-estimation

There are 1253 repositories under pose-estimation topic.

  • openpose

    CMU-Perceptual-Computing-Lab/openpose

    OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

    Language:C++30.2k9202k7.8k

  • MVIG-SJTU/AlphaPose

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

    Language:Python7.8k2061.1k2k
  • gluon-cv

    dmlc/gluon-cv

    Gluon CV Toolkit

    Language:Python5.8k1538281.2k

  • yeemachine/kalidokit

    Blendshape and kinematics calculator for Mediapipe/Tensorflow.js Face, Eyes, Pose, and Finger tracking models.

    Language:TypeScript5.2k810663
  • mmpose

    open-mmlab/mmpose

    OpenMMLab Pose Estimation Toolbox and Benchmark.

    Language:Python5.2k521.4k1.2k
  • DeepLabCut

    DeepLabCut/DeepLabCut

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

    Language:Python4.4k1271.8k1.6k

  • jinwchoi/awesome-action-recognition

    A curated list of action recognition and related area resources

    3.7k2079721

  • cvg/LightGlue

    LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

    Language:Python3.1k50100283

  • magicleap/SuperGluePretrainedNetwork

    SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

    Language:Python3.1k58138650
  • Hierarchical-Localization

    cvg/Hierarchical-Localization

    Visual localization made easy with hloc

    Language:Python2.9k87279545

  • roytseng-tw/Detectron.pytorch

    A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.

    Language:Python2.8k77207568
  • BlenderProc

    DLR-RM/BlenderProc

    A procedural Blender pipeline for photorealistic training image generation

    Language:Python2.6k45813433

  • cbsudux/awesome-human-pose-estimation

    A collection of awesome resources in Human Pose estimation.

    2.4k1264415

  • tryolabs/norfair

    Lightweight Python library for adding real-time multi-object tracking to any detector.

    Language:Python2.3k35159233

  • zju3dv/LoFTR

    Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022

    Language:Jupyter Notebook2.1k45214335

  • Daniil-Osokin/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.

    Language:Python2k34311475

  • Hzzone/pytorch-openpose

    pytorch implementation of openpose including Hand and Body Pose Estimation.

    Language:Jupyter Notebook2k2578389

  • IDEA-Research/DWPose

    "Effective Whole-body Pose Estimation with Two-stages Distillation" (ICCV 2023, CV4Metaverse Workshop)

    Language:Python2k2882132

  • axinc-ai/ailia-models

    The collection of pre-trained, state-of-the-art AI models for ailia SDK

    Language:Python1.9k49706310

  • IDEA-Research/detrex

    detrex is a research platform for DETR-based object detection, segmentation, pose estimation and other visual recognition tasks.

    Language:Python1.9k26154197
  • ICON

    YuliangXiu/ICON

    [CVPR'22] ICON: Implicit Clothed humans Obtained from Normals

    Language:Python1.6k42233219
  • ROMP

    Arthur151/ROMP

    Monocular, One-stage, Regression of Multiple 3D People and their 3D positions & trajectories in camera & global coordinates. ROMP[ICCV21], BEV[CVPR22], TRACE[CVPR2023]

    Language:Python1.3k41475226

  • tensorlayer/HyperPose

    Library for Fast and Flexible Human Pose Estimation

    Language:Python1.2k58184275

  • ViTAE-Transformer/ViTPose

    The official repo for [NeurIPS'22] "ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation" and [TPAMI'23] "ViTPose++: Vision Transformer for Generic Body Pose Estimation"

    Language:Python1.2k22131172

  • pypose/pypose

    A library for differentiable robotics.

    Language:Python1.2k12115101

  • zubair-irshad/Awesome-Implicit-NeRF-Robotics

    A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites

    1.2k77169

  • Jeff-sjtu/HybrIK

    Official code of "HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation", CVPR 2021

    Language:Python1.2k25221143
  • openpifpaf

    openpifpaf/openpifpaf

    Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.

    Language:Python1.1k34288249

  • eldar/pose-tensorflow

    Human Pose estimation with TensorFlow framework

    Language:C++1.1k57109384

  • bearpaw/pytorch-pose

    A PyTorch toolkit for 2D Human Pose Estimation.

    Language:Python1.1k31116251

  • tjiiv-cprg/EPro-PnP

    [CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

    Language:Python1.1k1487102

  • edvardHua/PoseEstimationForMobile

    :dancer: Real-time single person pose estimation for Android and iOS.

    Language:C++99853134269
  • AI-basketball-analysis

    chonyy/AI-basketball-analysis

    :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.

    Language:Python9373619179

  • DmitryRyumin/ICCV-2023-Papers

    ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!

    Language:Python885121038

  • Unity-Technologies/com.unity.perception

    Perception toolkit for sim2real training and validation in Unity

    Language:C#88537326172

  • FORTH-ModelBasedTracker/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

    Language:C++81933117133