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Related papers: Optical depth evaluation in pixel microlensing

200 papers

We present a deep learning system to infer the posterior distribution of a dense depth map associated with an image, by exploiting sparse range measurements, for instance from a lidar. While the lidar may provide a depth value for a small…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Yanchao Yang , Alex Wong , Stefano Soatto

Phase is a fundamental resource for optical imaging but cannot be directly observed with intensity measurements. The existing methods to quantify a phase distribution rely on complex devices and structures. Here we experimentally…

Optics · Physics 2020-03-25 Tengfeng Zhu , Junyi Huang , Zhichao Ruan

We develop a method of reconstructing the lensing field from lensed CMB temperature and polarization maps in real space as an alternative to the harmonic space estimators currently in use by extending an existing real space lensing…

Cosmology and Nongalactic Astrophysics · Physics 2018-02-07 Heather Prince , Kavilan Moodley , Jethro Ridl , Martin Bucher

In this paper, we deal with the problem of monocular depth estimation for fisheye cameras in a self-supervised manner. A known issue of self-supervised depth estimation is that it suffers in low-light/over-exposure conditions and in large…

Computer Vision and Pattern Recognition · Computer Science 2022-05-09 Qingan Yan , Pan Ji , Nitin Bansal , Yuxin Ma , Yuan Tian , Yi Xu

Accurate monocular depth estimation is crucial for 3D scene understanding, but existing methods often blur depth at object boundaries, introducing spurious intermediate 3D points. While achieving sharp edges usually requires very…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Aurélien Cecille , Stefan Duffner , Franck Davoine , Rémi Agier , Thibault Neveu

Monocular depth estimation has recently progressed beyond ordinal depth to provide metric depth predictions. However, its reliability in underwater environments remains limited due to light attenuation and scattering, color distortion,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Zijie Cai , Christopher Metzler

Perceiving 3D information is of paramount importance in many applications of computer vision. Recent advances in monocular depth estimation have shown that gaining such knowledge from a single camera input is possible by training deep…

Computer Vision and Pattern Recognition · Computer Science 2021-10-28 Sai Shyam Chanduri , Zeeshan Khan Suri , Igor Vozniak , Christian Müller

One of the important parameters for the assessment of glaucoma is optic nerve head (ONH) evaluation, which usually involves depth estimation and subsequent optic disc and cup boundary extraction. Depth is usually obtained explicitly from…

Image and Video Processing · Electrical Eng. & Systems 2020-07-16 Sharath M Shankaranarayana , Keerthi Ram , Kaushik Mitra , Mohanasankar Sivaprakasam

Scanning near-field optical microscopy is one of the most effective techniques for spectroscopy of nanoscale systems. However, inferring optical constants from the measured near-field signal can be challenging because of a complicated and…

Optics · Physics 2023-04-19 Yueqi Zhao , Xinzhong Chen , Ziheng Yao , Mengkun Liu , Michael M. Fogler

We study three-dimensional microlensing where two lenses are located at different distances along the line of sight. We formulate the lens equation in complex notations and recover several previous results. There are in total either 4 or 6…

Astrophysics of Galaxies · Physics 2015-06-17 Shude Mao , Hans J. Witt , Jin H. An

The simple physics of microlensing provides a well-understood tool with which to probe the atmospheres of distant stars in the Galaxy and Local Group with high magnification and resolution. Recent results in measuring stellar surface…

Astrophysics · Physics 2007-05-23 Penny D. Sackett

Estimation of time delays from a noisy and gapped data is one of the simplest data analysis problems in astronomy by its formulation. But as history of real experiments show, the work with observed data sets can be quite complex and…

Instrumentation and Methods for Astrophysics · Physics 2011-05-31 A. Hirv , N. Olspert , J. Pelt

We consider a contribution of microlensing to the X-ray variability of high-redshifted QSOs. Cosmologically distributed gravitational microlenses could be localized in galaxies (or even in bulge or halo of gravitational macrolenses) or…

Astrophysics · Physics 2009-11-10 Alexander F. Zakharov , Luka C. Popovic , Predrag Jovanovic

Polarization data will soon provide the best avenue for measurements of the CMB lensing potential, although it is potentially sensitive to several instrumental effects including beam asymmetry, polarization angle uncertainties, sky…

Cosmology and Nongalactic Astrophysics · Physics 2019-06-10 Toshiya Namikawa , Ryuichi Takahashi

The most important uncertainty in the results of gravitational microlensing experiments comes from the difficulties of photometry caused by blending of source stars. Recently Nemiroff (1997) pointed out that the results of microlensing…

Astrophysics · Physics 2007-05-23 Seunghun Lee , Cheongho Han

I present a somewhat selective review of microlensing theory, covering five major areas: 1) the derivation of the basic formulae, 2) the relation between the observables and the fundamental physical parameters, 3) binaries, 4) astrometric…

Astrophysics · Physics 2007-05-23 Andrew Gould

Measurements of the microlensing optical depth and event rate toward the Large Magellanic Cloud (LMC) can be used to probe the distribution and mass function of compact objects in the direction toward that galaxy - in the Milky Way disk,…

This paper is devoted to exploring how we can discover and study nearby (< 1-2 kpc) planetary and binary systems by observing their action as gravitational lenses. Lensing can extend the realm of nearby binaries and planets that can be…

Astrophysics · Physics 2008-01-11 R. Di Stefano

Data depth is a concept in multivariate statistics that measures the centrality of a point in a given data cloud in $\IR^d$. If the depth of a point can be represented as the minimum of the depths with respect to all one-dimensional…

Computation · Statistics 2020-07-17 Rainer Dyckerhoff , Pavlo Mozharovskyi , Stanislav Nagy