This book is the result of a seminar in which we reviewed multimodal
approaches and attempted to create a solid overview of the field, starting with
the current state-of-the-art approaches in the two subfields of Deep Learning
individually. Further, modeling frameworks are discussed where one modality is
transformed into the other, as well as models in which one modality is utilized
to enhance representation learning for the other. To conclude the second part,
architectures with a focus on handling both modalities simultaneously are
introduced. Finally, we also cover other modalities as well as general-purpose
multi-modal models, which are able to handle different tasks on different
modalities within one unified architecture. One interesting application
(Generative Art) eventually caps off this booklet.

这篇论文概述了多模态方法中的最新技术和框架，并重点介绍了 Deep Learning、模型框架、特征表示学习以及生成艺术等关键点。