Single-photon avalanche diodes (SPADs) are promising detector technologies that may be used to achieve active 3D imaging systems with fast acquisition, high timing accuracy and high detection sensitivity. Such systems have broad applications in the domains of biological imaging, remote sensing and robotics. However, the detectors face technical impairments known as pileup that cause measurement distortions to limit their precision. In a recent study, conducted at the Stanford University Department of Electrical Engineering, scientists Felix Heide and co-workers developed a probabilistic image formation model that could accurately model pileup. Using the proposed model, the scientists devised inverse methods to efficiently and robustly estimate the scene depth and reflectance from recorded photon counts. With the algorithm, they were able to demonstrate improvements to the accuracy of timing, compared to existing techniques. More importantly, the model allowed accuracy at the sub-picosecond in photon-efficient 3D imaging for the first time in practical scenarios, whereas previously only widely-varying photon counts were observed. The results are now published in Scientific Reports.