activity
20192022
most citedZeroEGGS: Zero-shot Example-based Gesture Generation from Speech

10 citations · 10 across the 1 of their papers we have counts for

collaborators

5 papers

cs.GR202210 cited

ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech

Saeed Ghorbani, Ylva Ferstl, Daniel Holden +2

We present ZeroEGGS, a neural network framework for speech-driven gesture generation with zero-shot style control by example. This means style can be controlled via only a short ex…

cs.GR2020

Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model

Saeed Ghorbani, Calden Wloka, Ali Etemad +2

We present a probabilistic framework to generate character animations based on weak control signals, such that the synthesized motions are realistic while retaining the stochastic…

cs.CV2020

Gait Recognition using Multi-Scale Partial Representation Transformation with Capsules

Alireza Sepas-Moghaddam, Saeed Ghorbani, Nikolaus F. Troje +1

Gait recognition, referring to the identification of individuals based on the manner in which they walk, can be very challenging due to the variations in the viewpoint of the camer…

cs.CV2019

Auto-labelling of Markers in Optical Motion Capture by Permutation Learning

Saeed Ghorbani, Ali Etemad, Nikolaus F. Troje

Optical marker-based motion capture is a vital tool in applications such as motion and behavioural analysis, animation, and biomechanics. Labelling, that is, assigning optical mark…

cs.CV2019

AMASS: Archive of Motion Capture as Surface Shapes

Naureen Mahmood, Nima Ghorbani, Nikolaus F. Troje +2

Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions…