  Extracting behavioral measurements non-invasively from video is stymied by
the fact that it is a hard computational problem. Recent advances in deep
learning have tremendously advanced predicting posture from videos directly,
which quickly impacted neuroscience and biology more broadly. In this primer we
review the budding field of motion capture with deep learning. In particular,
we will discuss the principles of those novel algorithms, highlight their
potential as well as pitfalls for experimentalists, and provide a glimpse into
the future.
