Recurrent neural networks are prime candidates for learning relationships and evolutions in multi-dimensional time series data. The performance of such a network is judged by the loss function, which is aggregated into a ...

We present a method for the stylization of mountainous terrains that allows creating abstract representations in different rendering styles. Our method consists of two major components: structure-aware terrain filtering ...