  We introduce Omni-LOS, a neural computational imaging method for conducting
holistic shape reconstruction (HSR) of complex objects utilizing a
Single-Photon Avalanche Diode (SPAD)-based time-of-flight sensor. As
illustrated in Fig. 1, our method enables new capabilities to reconstruct
near-$360^\circ$ surrounding geometry of an object from a single scan spot. In
such a scenario, traditional line-of-sight (LOS) imaging methods only see the
front part of the object and typically fail to recover the occluded back
regions. Inspired by recent advances of non-line-of-sight (NLOS) imaging
techniques which have demonstrated great power to reconstruct occluded objects,
Omni-LOS marries LOS and NLOS together, leveraging their complementary
advantages to jointly recover the holistic shape of the object from a single
scan position. The core of our method is to put the object nearby diffuse walls
and augment the LOS scan in the front view with the NLOS scans from the
surrounding walls, which serve as virtual ``mirrors'' to trap lights toward the
object. Instead of separately recovering the LOS and NLOS signals, we adopt an
implicit neural network to represent the object, analogous to NeRF and NeTF.
While transients are measured along straight rays in LOS but over the spherical
wavefronts in NLOS, we derive differentiable ray propagation models to
simultaneously model both types of transient measurements so that the NLOS
reconstruction also takes into account the direct LOS measurements and vice
versa. We further develop a proof-of-concept Omni-LOS hardware prototype for
real-world validation. Comprehensive experiments on various wall settings
demonstrate that Omni-LOS successfully resolves shape ambiguities caused by
occlusions, achieves high-fidelity 3D scan quality, and manages to recover
objects of various scales and complexity.

Computer Vision and Pattern Recognition;Image and Video Processing