Single-photon light detection and ranging (Lidar) devices can be used to obtain range and reflectivity information from 3D scenes. However, reconstructing the 3D surfaces from the raw waveforms can be very challenging, in particular when the number of spurious background detections is large compared to the number of signal detections. This paper introduces a new and fast detection algorithm, which can be used to assess the presence of objects/surfaces in each waveform, allowing only the histograms where the imaged surfaces are present to be further processed. The method is compared to state-of-the-art 3D reconstruction methods using synthetic and real single-photon data and the results illustrate its benefits for fast and robust target detection using single-photon data.