Basic Concepts
Human Pose Estimation 101
Introduction to Pose Estimation: How Machines Understand Human MotionLearn the fundamentals of Human Pose Estimation (HPE), how it works, and its applications in AI-powered motion tracking.
Datasets for Human Pose Estimation
Essential Datasets for Training Pose Estimation ModelsExplore the most widely used datasets for 2D and 3D pose estimation, including COCO, MPII, and Human3.6M.
Pose Representation Formats
Understanding Different Ways to Represent Human Pose DataLearn about keypoint-based representations, body mesh models, and other formats used to represent human pose data in machine learning.
Simple Baselines for Human Pose Estimation
Minimalist Approaches to 2D & 3D Pose EstimationLearn about simple yet effective baseline models used in pose estimation, their strengths, and when to use them.
Common Loss Functions for Pose Estimation
Key Loss Functions for Training Accurate Pose ModelsUnderstand essential loss functions, such as MSE, L1, and heatmap-based losses, used to optimize pose estimation networks.
Standard Evaluation Metrics
Measuring Pose Estimation Performance with ConfidenceDiscover the key evaluation metrics—like PCK, MPJPE, and AUC—used to assess the accuracy and reliability of pose estimation models.
Challenges in Human Pose Estimation
Common Problems and How They Impact Model PerformanceOverview of common challenges in human pose estimation, such as occlusions, viewpoint variations, and domain shift.
