Deep Generative Models for learning Coherent Latent Representations from Multi-Modal Data

ICLR 2019 Timo KorthalsMarc HesseJürgen Leitner

The application of multi-modal generative models by means of a Variational Auto Encoder (VAE) is an upcoming research topic for sensor fusion and bi-directional modality exchange. This contribution gives insights into the learned joint latent representation and shows that expressiveness and coherence are decisive properties for multi-modal datasets... (read more)

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