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Pose2Muscle reformulates muscle estimation as a structured prediction problem over discrete muscle activity states, yielding a more stable and interpretable target space and suggesting the potential of Pose2Muscle for muscle-aware movement analysis when direct physiological sensing is impractical.
Explicitly modeling human-object interactions boosts multi-person human mesh recovery accuracy by up to 9.9%, showing that interaction context is key to understanding human pose and shape in complex scenes.
Current multimodal models can't handle the rapid-fire tactical analysis required for boxing commentary, as revealed by a new dataset and evaluation framework.
