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Representing motion as a sequence of latent primitives, a flexible
  approach for human motion modelling

Representing motion as a sequence of latent primitives, a flexible approach for human motion modelling

27 June 2022
Mathieu Marsot
Stefanie Wuhrer
Jean-Sébastien Franco
Anne Hélene Olivier
ArXivPDFHTML

Papers citing "Representing motion as a sequence of latent primitives, a flexible approach for human motion modelling"

2 / 2 papers shown
Title
Probabilistic Character Motion Synthesis using a Hierarchical Deep
  Latent Variable Model
Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model
Saeed Ghorbani
C. Wloka
Ali Etemad
M. Brubaker
N. Troje
3DV
28
31
0
20 Oct 2020
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
219
13,886
0
02 Dec 2016
1