  Online auction has been very widespread in the recent years. Platform
administrators are working hard to refine their auction mechanisms that will
generate high profits while maintaining a fair resource allocation. With the
advancement of computing technology and the bottleneck in theoretical
frameworks, researchers are shifting gears towards online auction designs using
deep learning approaches. In this article, we summarized some common deep
learning infrastructures adopted in auction mechanism designs and showed how
these architectures are evolving. We also discussed how researchers are
tackling with the constraints and concerns in the large and dynamic industrial
settings. Finally, we pointed out several currently unresolved issues for
future directions.
