FatigueFusion fuses fatigue features in latent space using algorithmic, data-driven, and PINN modules to synthesize novel fatigued motions from non-fatigued joint sequences in an end-to-end pipeline.
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Fatigue-PINN applies physics-informed neural networks to simulate fatigue effects on human motion using a three-compartment muscle model for joint torque modulation in motion synthesis.
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FatigueFusion: Latent Space Fusion for Fatigue-Driven Motion Synthesis
FatigueFusion fuses fatigue features in latent space using algorithmic, data-driven, and PINN modules to synthesize novel fatigued motions from non-fatigued joint sequences in an end-to-end pipeline.
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Fatigue-PINN: Physics-Informed Fatigue-Driven Motion Modulation and Synthesis
Fatigue-PINN applies physics-informed neural networks to simulate fatigue effects on human motion using a three-compartment muscle model for joint torque modulation in motion synthesis.