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Single-photon lidar has emerged as a prime candidate technology for depthimaging through challenging environments. Until now, a major limitation hasbeen the significant amount of time required for the analysis of the recordeddata. Here we show a new computational framework for real-timethree-dimensional (3D) scene reconstruction from single-photon data. Bycombining statistical models with highly scalable computational tools from thecomputer graphics community, we demonstrate 3D reconstruction of complexoutdoor scenes with processing times of the order of 20 ms, where the lidardata was acquired in broad daylight from distances up to 320 metres. Theproposed method can handle an unknown number of surfaces in each pixel,allowing for target detection and imaging through cluttered scenes. Thisenables robust, real-time target reconstruction of complex moving scenes,paving the way for single-photon lidar at video rates for practical 3D imagingapplications.

Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers