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Research map / 3D vision / Face and shape

Scalable Dense Non-Rigid Structure-From-Motion: A Grassmannian Perspective

CVPR 2018 · 3D vision › Face and shape · approach: Articulated and non-rigid shape learning · 52 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the spatio-temporal Grassmannian method instead of DVDense NRSfM · Synthetic face sequences 1–4e3D: 0.0531 -> 0.0443; 0.0457 -> 0.0381; 0.0346 -> 0.0294; 0.0379 -> 0.0309Helped
Use the spatio-temporal Grassmannian method instead of DSDense NRSfM · kinect_paper and kinect_tshirte3D: 0.0612 -> 0.0394; 0.0636 -> 0.0362Helped
Add the spatial constraint to the formulation (ablation)Proposed method · Synthetic face sequencese3DHelped
Add the temporal constraint to the formulation (ablation)Proposed method · Synthetic face sequencese3DHelped
Use a small number of eigenvalues for each local structure instead of all eigenvalues (ablation)Proposed method · Noise-free sequencese3DNo clear effect
Increase the number of local subspaces beyond a certain value (ablation)Proposed method · Noise-free sequencese3DNo clear effect
Add Gaussian noise to the measurement matrixProposed method · Synthetic face and kinect sequencese3DNo clear effect

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