Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …

Emerging single-photon-sensitive sensors produce picosecond-accurate time-stamped
photon counts. Applying advanced inverse methods to process these data has resulted in …

Imaging objects outside a camera's direct line of sight has important applications in robotic
vision, remote sensing, and many other domains. Time-of-flight-based non-line-of-sight …

Computing the amounts of light arriving from different directions enables a diffusely
reflecting surface to play the part of a mirror in a periscope—that is, perform non-line-of-sight …

Non-line-of-sight imaging allows objects to be observed when partially or fully occluded from
direct view, by analysing indirect diffuse reflections off a secondary relay surface. Despite …

We present a novel theory of Fermat paths of light between a known visible scene and an
unknown object not in the line of sight of a transient camera. These light paths either obey …

Conventional sensor systems record information about directly visible objects, whereas
occluded scene components are considered lost in the measurement process. Non-line-of …

We show that walls and other obstructions with edges can be exploited as naturally-
occurring" cameras" that reveal the hidden scenes beyond them. In particular, we …

Imaging through fog has important applications in industries such as self-driving cars,
augmented driving, airplanes, helicopters, drones and trains. Here we show that time …

Objects obscured by occluders are considered lost in the images acquired by conventional
camera systems, prohibiting both visualization and understanding of such hidden objects …