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

Many computer vision techniques infer properties of our physical world from images.
Although images are formed through the physics of light and mechanics, computer vision …

Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …

The last decade has seen the development of a wide set of tools, such as wavefront
sha**, computational or fundamental methods, that allow us to understand and control …

Non–line-of-sight (NLOS) imaging has the ability to reconstruct hidden objects from indirect
light paths that scatter multiple times in the surrounding environment, which is of …

The presence of a scattering medium in the imaging path between an object and an
observer is known to severely limit the visual acuity of the imaging system. We present an …

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

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only
measurements. As it pervades a broad variety of applications, many researchers have …

Imaging through nonstatic scattering media is one of the major challenges in optics, and
encountered in imaging through dense fog, turbid water, and many other situations. Here …

Optical cryptanalysis is essential to the further investigation of more secure optical
cryptosystems. Learning-based attack of optical encryption eliminates the need for the …