As an emerging technology that has attracted huge attention, non-line-ofsight (NLOS)
imaging can reconstruct hidden objects by analyzing the diffuse reflection on a relay surface …

We present a neural modeling framework for non-line-of-sight (NLOS) imaging. Previous
solutions have sought to explicitly recover the 3D geometry (eg, as point clouds) or voxel …

Non-line-of-sight (NLOS) imaging techniques have the ability to look around corners, which
is of growing interest for diverse applications. We explore compressed sensing in active …

Active confocal non-line-of-sight (NLOS) imaging has successfully enabled seeing around
corners relying on high-quality transient measurements. However, acquiring spatial-dense …

Non-line-of-sight (NLOS) imaging techniques have the ability to look around corners, which
attracts growing interest for diverse applications in autonomous navigation, medicine …

Passive non-line-of-sight (NLOS) imaging has potential applications in autonomous driving
and search and rescue, but current deep learning approaches often produce suboptimal …

Passive non-line-of-sight (NLOS) imaging is a promising technique to enhance visual
perception for the occluded object hidden behind the wall. Here we present a data-driven …

This paper aims to facilitate more practical NLOS imaging by reducing the number of
samplings and scan areas. To this end, we introduce a phasor-based enhancement network …

Abstract Non-line-of-sight (NLOS) imaging aims at reconstructing the location, shape,
albedo, and surface normal of the hidden object around the corner with measured transient …

This paper introduces 3DFIRES a novel system for scene-level 3D reconstruction from
posed images. Designed to work with as few as one view 3DFIRES reconstructs the …