  We survey a number of data visualization techniques for analyzing Computer
Vision (CV) datasets. These techniques help us understand properties and latent
patterns in such data, by applying dataset-level analysis. We present various
examples of how such analysis helps predict the potential impact of the dataset
properties on CV models and informs appropriate mitigation of their
shortcomings. Finally, we explore avenues for further visualization techniques
of different modalities of CV datasets as well as ones that are tailored to
support specific CV tasks and analysis needs.
