Traditional imaging systems, such as the eye or cameras, image scenes that lie in the direct line-of-sight (LoS). Most objects are opaque in the optical and infrared regimes and can limit dramatically the field of view (FoV). Current approaches to see around occlusions exploit the multireflection propagation of signals from neighboring surfaces either in the microwave or the optical bands. Using lower frequency signals anatomical information is limited and images suffer from clutter while optical systems encounter diffuse scattering from most surfaces and suffer from path loss, thus limiting the imaging distance. In this work, we show that terahertz (THz) waves can be used to extend visibility to non-line-of-sight (NLoS) while combining the advantages of both spectra. The material properties and roughness of most building surfaces allow for a unique combination of both diffuse and strong specular scattering. As a result, most building surfaces behave as lossy mirrors that enable propagation paths between a THz camera and the NLoS scenes. We propose a mirror folding algorithm that tracks the multireflection propagation of THz waves to 1) correct the image from cluttering and 2) see around occlusions without a priori knowledge of the scene geometry and material properties. To validate the feasibility of the proposed NLoS imaging approach, we carried out a numerical analysis and developed two THz imaging systems to demonstrate real-world NLoS imaging experiments in sub-THz bands (270-300 GHz). The results show the capability of THz radar imaging systems to recover both the geometry and pose of LoS and NLoS objects with centimeter-scale resolution in various multipath propagation scenarios. THz NLoS imaging can operate in low visibility conditions (e.g., night, strong ambient light, smoke) and uses computationally inexpensive image reconstruction algorithms.