Image Skeleton Recognition Methods
OpenPose
An open-source library for multi-person pose estimation. It detects key points on the human body, including joints and skeletal connections, using deep learning techniques with convolutional neural networks (CNNs).
An open-source library for multi-person pose estimation. It detects key points on the human body, including joints and skeletal connections, using deep learning techniques with convolutional neural networks (CNNs).
DeepPose
A method proposed by Microsoft that uses deep learning for estimating key points on the human body. It employs CNNs for end-to-end pose estimation by directly predicting joint positions from images.
A method proposed by Microsoft that uses deep learning for estimating key points on the human body. It employs CNNs for end-to-end pose estimation by directly predicting joint positions from images.
PoseNet
Developed by Google, PoseNet is a lightweight real-time pose estimation system. It uses CNNs to detect key points on the human body and is suitable for applications requiring real-time performance. HRNet (High-Resolution Network)
An advanced pose estimation method that focuses on high-resolution feature representations. It maintains and merges multi-scale feature maps to improve the accuracy of key point detection.
Developed by Google, PoseNet is a lightweight real-time pose estimation system. It uses CNNs to detect key points on the human body and is suitable for applications requiring real-time performance. HRNet (High-Resolution Network)
An advanced pose estimation method that focuses on high-resolution feature representations. It maintains and merges multi-scale feature maps to improve the accuracy of key point detection.
AlphaPose
An open-source multi-person pose estimation library based on PyTorch. It uses CNNs and confidence maps to detect key points and supports both single-person and multi-person pose estimation.
An open-source multi-person pose estimation library based on PyTorch. It uses CNNs and confidence maps to detect key points and supports both single-person and multi-person pose estimation.
MPII Human Pose Dataset
A widely used dataset for training and evaluating pose estimation models. It contains images with various poses and environments, suitable for training deep learning models.
A widely used dataset for training and evaluating pose estimation models. It contains images with various poses and environments, suitable for training deep learning models.
Stacked Hourglass Network
A design for human pose estimation that stacks Hourglass modules. It operates at multiple scales, making it suitable for different body sizes.
A design for human pose estimation that stacks Hourglass modules. It operates at multiple scales, making it suitable for different body sizes.
Detectron2
Developed by Facebook AI Research (FAIR), Detectron2 is a general-purpose framework for object detection and instance segmentation. It can be used for detecting key points on the human body.
Developed by Facebook AI Research (FAIR), Detectron2 is a general-purpose framework for object detection and instance segmentation. It can be used for detecting key points on the human body.
LEAP (Learning Articulated Occupancy of People)
A method for 3D human pose estimation that predicts joint positions by regressing articulated occupancy maps.
A method for 3D human pose estimation that predicts joint positions by regressing articulated occupancy maps.
EfficientPose
A lightweight pose estimation method designed for real-time performance, using a combination of lightweight network structures and model compression techniques.
A lightweight pose estimation method designed for real-time performance, using a combination of lightweight network structures and model compression techniques.
Integral Human Pose Regression
This method regresses integral heatmaps for entire human body pose detection, with each heatmap corresponding to a joint's position.
This method regresses integral heatmaps for entire human body pose detection, with each heatmap corresponding to a joint's position.
SimpleBaseline
An effective yet simple pose estimation method that stacks Hourglass modules at different scales and connects key points with a simple baseline.
An effective yet simple pose estimation method that stacks Hourglass modules at different scales and connects key points with a simple baseline.
DeepLabCut
An open-source framework based on deep learning for pose estimation and behavior analysis. It provides a toolchain for training and evaluating custom models.
An open-source framework based on deep learning for pose estimation and behavior analysis. It provides a toolchain for training and evaluating custom models.
MultiPoseNet
A framework for multi-person pose estimation that can simultaneously detect key points for multiple individuals. It uses cascaded convolutional network structures suitable for multi-person scenarios.
A framework for multi-person pose estimation that can simultaneously detect key points for multiple individuals. It uses cascaded convolutional network structures suitable for multi-person scenarios.
HMR (Human Mesh Recovery)
HMR is a method that achieves human body pose estimation and reconstruction by mapping images onto a three-dimensional human body mesh. It focuses not only on key points but also provides an estimation of the entire human body shape.
HMR is a method that achieves human body pose estimation and reconstruction by mapping images onto a three-dimensional human body mesh. It focuses not only on key points but also provides an estimation of the entire human body shape.
HRNet-3D
HRNet-3D extends HRNet to perform three-dimensional pose estimation. It enhances modeling capabilities for deep details by jointly optimizing two-dimensional and three-dimensional information.
HRNet-3D extends HRNet to perform three-dimensional pose estimation. It enhances modeling capabilities for deep details by jointly optimizing two-dimensional and three-dimensional information.
SPIGOT
SPIGOT is a method for human body skeleton estimation that leverages information from image semantic segmentation to improve the accuracy of key point detection.
SPIGOT is a method for human body skeleton estimation that leverages information from image semantic segmentation to improve the accuracy of key point detection.
PifPaf
PifPaf is a method for jointly detecting human body key points and poses. It enhances overall model performance by simultaneously handling multiple tasks.
PifPaf is a method for jointly detecting human body key points and poses. It enhances overall model performance by simultaneously handling multiple tasks.
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