29 papers with code • 2 benchmarks • 3 datasets
Generation of gestures, as a sequence of 3d poses
LibrariesUse these libraries to find Gesture Generation models and implementations
On the other hand, all synthetic motion is found to be vastly less appropriate for the speech than the original motion-capture recordings.
Specifically, we perform cross-modal translation from "in-the-wild'' monologue speech of a single speaker to their hand and arm motion.
In this paper, we present an automatic gesture generation model that uses the multimodal context of speech text, audio, and speaker identity to reliably generate gestures.
We evaluate different representation sizes in order to find the most effective dimensionality for the representation.
In interactive scenarios, systems for generating natural animations on the fly are key to achieving believable and relatable characters.
Moving fast and slow: Analysis of representations and post-processing in speech-driven automatic gesture generation
We provide an analysis of different representations for the input (speech) and the output (motion) of the network by both objective and subjective evaluations.
A key challenge, called gesture style transfer, is to learn a model that generates these gestures for a speaking agent 'A' in the gesturing style of a target speaker 'B'.
We study relationships between spoken language and co-speech gestures in context of two key challenges.