The single-photon sensitivity and picosecond time resolution of single-photon light detection and ranging (LiDAR) can provide a full-waveform profile for retrieving the three-dimentional (3D) profile of the target separated from foreground clutter. This capability has made single-photon LiDAR a solution for imaging through obscurant, camouflage nets, and semitransparent materials. However, the obstructive presence of the clutter and limited pixel numbers of single-photon detector arrays still pose challenges in achieving high-quality imaging. Here, we demonstrate a single-photon array LiDAR system combined with tailored computational algorithms for high-resolution 3D imaging through camouflage nets. For static targets, we develop a 3D sub-voxel scanning approach along with a photon-efficient deconvolution algorithm. Using this approach, we demonstrate 3D imaging through camouflage nets with a 3× improvement in spatial resolution and a 7.5× improvement in depth resolution compared with the inherent system resolution. For moving targets, we propose a motion compensation algorithm to mitigate the net’s obstructive effects, achieving video-rate imaging of camouflaged scenes at 20 frame/s. More importantly, we demonstrate 3D imaging for complex scenes in various outdoor scenarios and evaluate the advanced features of single-photon LiDAR over a visible-light camera and a mid-wave infrared (MWIR) camera. The results point a way forward for high-resolution real-time 3D imaging of multi-depth scenarios.