This is the first comprehensive survey of LiDAR in rehabilitation, summarizing applications, AI techniques, trends, gaps, and future directions across studies from 2019-2025.
Human- m3: A multi-view multi-modal dataset for 3d human pose estimation in outdoor scenes
2 Pith papers cite this work. Polarity classification is still indexing.
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MAEM is a training-free framework that combines monocular 3D mesh recovery with a two-stage epipolar matching strategy using disjoint-set-union clustering and per-joint triangulation for multi-view multi-person 3D pose estimation in basketball.
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Mesh-Aware Epipolar Matching for Multi-View Multi-Person 3D Pose Estimation in Basketball
MAEM is a training-free framework that combines monocular 3D mesh recovery with a two-stage epipolar matching strategy using disjoint-set-union clustering and per-joint triangulation for multi-view multi-person 3D pose estimation in basketball.