The computational sensing community has recently seen a surge of works on imaging
beyond the direct line of sight. However, most of the reported results rely on drastically
different measurement setups and algorithms, and are therefore hard to impossible
to compare quantitatively. In this paper, we focus on an important class of approaches,
namely those that aim to reconstruct scene properties from time-resolved optical impulse
responses. We introduce a collection of reference data and quality metrics that are tailored
to the most common use cases, and we define reconstruction challenges that we
hope will aid the development and assessment of future methods.