MVIG-SJTU/AlphaPose
AlphaPose
AlphaPose 是一个深度学习姿态估计框架和 PyTorch 计算机视觉库，旨在检测和追踪图像及视频中的人体、面部、手部和足部关键点。它提供了一套用于骨骼姿态估计和多人姿态追踪的系统。
该项目实现了三维人体姿态重建工具，可从二维图像数据生成关节位置和人体网格形状。它还包含一个多人姿态追踪器，能够在连续的视频帧中保持多人的身份识别。
该框架涵盖了广泛的计算机视觉功能，包括多人关键点定位、人体运动追踪以及三维人体网格重建。
Features
- Pose Estimation - Provides a deep learning framework for detecting and marking human body, face, hand, and foot keypoints for multiple people.
- PyTorch Computer Vision Pipelines - Provides a comprehensive PyTorch-based computer vision pipeline for human pose estimation and motion tracking.
- Human - Detects keypoints for the human body, face, hands, and feet across multiple people in images and videos.
- Keypoint Detection - Locates specific anatomical points on the human body, face, hands, and feet for computer vision analysis.
- Multi-Person Keypoint Localization - Finds and marks keypoints for the human body, face, hands, and feet across multiple people in images.
- Multi-Person Trackers - Identifies and maintains the identity of multiple people across consecutive video frames using a pose tracking pipeline.
- Top-Down Pipelines - Implements a top-down pipeline that detects human bounding boxes before predicting keypoints within them.
- Pose Estimation Frameworks - Provides a deep learning system for detecting and tracking human body, face, hand, and foot keypoints in images and videos.
- 3D Pose Estimation - Calculates three-dimensional joint positions and body mesh shapes from two-dimensional image data.
- 3D Pose Reconstruction - Generates three-dimensional body representations and meshes from two-dimensional image data.
- Graph Compiler Acceleration - Uses a dynamic computation graph and just-in-time compilation via Jittor to accelerate training and inference.
- Multi-Stage Regression - Predicts keypoint locations through iterative refinement of confidence maps to increase spatial accuracy.
- Region Proposal Filtering - Filters potential person detections using a regional proposal network to isolate individual human figures.
- Temporal Pose Analysis - Matches detected skeletal poses across video frames by comparing spatial proximity and appearance features.
- Human Motion Analysis - Monitors motion and trajectory by maintaining the identity of detected persons across video frames.
- Video Pose Estimation - Matches poses from the same person across consecutive frames to ensure consistent identity in video sequences.
- 2D-to-3D Mesh Lifting - Implements tools to generate three-dimensional joint positions and body mesh shapes from two-dimensional image data.
- Real-Time Motion Tracking - Monitors human movement and identity across video frames by maintaining consistent skeletal posture tracking.
- Computer Vision Libraries - System for real-time multi-person pose estimation and tracking.
- Pose Estimation Frameworks - High-accuracy multi-person pose estimation system.
- Real-time Estimation - High-accuracy multi-person pose estimation system.
