Limitations of (Procrustes) Alignment in Assessing Multi-Person Human Pose and Shape Estimation
We delve into the challenges of accurately estimating 3D human pose and shape in video surveillance scenarios. Beginning with the advocacy for metrics like W-MPJPE and W-PVE, which omit the (Procrustes) realignment step, to improve model evaluation, we then introduce RotAvat. This technique aims to enhance these metrics by refining the alignment of 3D meshes with the ground plane. Through qualitative comparisons, we demonstrate RotAvat's effectiveness in addressing the limitations of existing aproaches.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A Novel Procrustes Analysis Method to Quantify Multi-Joint Coordination of the Upper Extremity after Stroke
Upper extremity motor impairment affects about 80\% of persons after strokes. For stroke rehabilitation, upper limb kinematic assessments have increasingly been used as primary or secondary outcome measures. Studying the…
Unsupervised Alignment of Embeddings with Wasserstein Procrustes
A library for Multilingual Unsupervised or Supervised word Embeddings
Word EmbeddingsHyperbolic Procrustes Analysis Using Riemannian Geometry
Label-free alignment between datasets collected at different times, locations, or by different instruments is a fundamental scientific task. Hyperbolic spaces have recently provided a fruitful foundation for the developm…
Computational EfficiencyTranslationKernel Hyperalignment
We offer a regularized, kernel extension of the multi-set, orthogonal Procrustes problem, or hyperalignment. Our new method, called Kernel Hyperalignment, expands the scope of hyperalignment to include nonlinear measures…
Multi-Way Representation Alignment
The Platonic Representation Hypothesis suggests that independently trained neural networks converge to increasingly similar latent spaces. However, current strategies for mapping these representations are inherently pair…