https://www.selleckchem.com/products/gdc-0077.html
This paper presents a hybrid animation approach that combines example-based and neural animation methods to create a simple, yet powerful animation regime for human faces. Example-based methods usually employ a database of pre-recorded sequences that are concatenated or looped in order to synthesize novel animations. In contrast to this traditional example-based approach, we introduce a light-weight auto-regressive network to transform our animation-database into a parametric model. During training, our network learns the dynamics of f
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