Beyond MPJPE: A Physics-Based Audit of Monocular 3D Human Pose Estimation
Keywords: 3D human pose estimation, physical plausibility, evaluation metrics, physics-based analysis, SMPL, monocular reconstruction, foot skating, temporal smoothness, motion quality, benchmark
TL;DR: We propose PhysScore a training-free physics metric to measure physics plausibility of 3D pose methods, showing MPJPE rankings diverge significantly from physical realism. Simple post-processing improves physics by 27%.
Abstract: Monocular 3D human pose estimation has advanced rapidly, with methods achieving increasingly low Mean Per-Joint Position Error (MPJPE) on standard benchmarks. However, MPJPE measures only geometric accuracy and is agnostic to whether the estimated motion is physically plausible—a property critical for downstream applications such as character animation, biomechanical analysis, and augmented reality. We introduce PHYSSCORE, a training-free composite metric comprising six physics-based sub-metrics: foot skating, ground penetration, temporal smoothness, joint angle limit violations, self-penetration, and center-of-mass stability. PHYSSCORE operates directly on estimated SMPL joint positions and requires no ground truth. We conduct a systematic audit of six state-of-the-art monocular methods on the 3DPW benchmark, including real outputs from WHAM, HybrIK, and PARE. Our analysis reveals that MPJPE and PHYSSCORE are only weakly correlated (Spearman ρ=0.37), with significant rank reversals: the temporal method WHAM ranks 3rd in MPJPE but 1st in physical plausibility. We further show that simple physics-aware post-processing—joint-limit clamping, temporal smoothing, and ground-plane correction—consistently improves PHYSSCORE across all methods. We release PHYSSCORE as an open-source evaluation tool to complement geometric metrics at https://github.com/mujtabahasan/physscore.
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Submission Number: 15
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