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Global Auto-regressive Depth Recovery via Iterative Non-local Filtering

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Publications associées (33)

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Towards Real-World Super-Resolution using Deep Neural Networks

Ruofan Zhou

Image super-resolution reconstructs a higher-resolution image from the observed low-resolution image. In recent years, machine learning models have been widely employed and deep learning networks have achieved state-of-the-art super-resolution performance. ...

EPFL2020

Model-based 3D Face Reconstruction

Christophe René Joseph Ecabert

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

EPFL2021

Image Compression and Quality Assessment using Convolutional Neural Networks

Pinar Akyazi

The rapid development of digital imaging and video has placed visual contents in the heart of our lives. Digital multimedia span a vast number of areas from business to leisure, including but not limited to education, medicine, accessibility, training, adv ...

EPFL2020

Direct time-of-flight SPAD image sensors for light detection and ranging

Preethi Padmanabhan

Depth sensing is an increasingly important feature in many applications of consumer, automotive, augmented/virtual reality (AR-VR), space and bio-medical imaging. Long range, high depth resolution, high spatial resolution, and high frame rates are often co ...

EPFL2021

Robust Differentiable SVD

Pascal Fua, Mathieu Salzmann, Wei Wang, Yinlin Hu, Zheng Dang

Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

2021

A Pixel Design of a Branching Ultra-Highspeed Image Sensor

Edoardo Charbon

A burst image sensor named Hanabi, meaning fireworks in Japanese, includes a branching CCD and multiple CMOS readout circuits. The sensor is backside-illuminated with a light/charge guide pipe to minimize the temporal resolution by suppressing the horizont ...

2021

Fat navigators and Moire phase tracking comparison for motion estimation and retrospective correction

Daniel Gallichan, Frédéric Gretsch

Purpose To compare motion tracking by 2 modern methods (fat navigators [FatNavs] and Moir' phase tracking [MPT]) as well as their performance for retrospective correction of very high resolution acquisitions. Methods A direct comparison of FatNavs and MPT ...

Wiley2020

Compress-and-restart block Krylov subspace methods for Sylvester matrix equations

Kathryn Dianne Lund, Daniel Kressner, Stefano Massei

Block Krylov subspace methods (KSMs) comprise building blocks in many state-of-the-art solvers for large-scale matrix equations as they arise, for example, from the discretization of partial differential equations. While extended and rational block Krylov ...

2020

Perspectives and limitations of visible-thermal image pair synthesis via generative adversarial networks

Michael Stefan Daniel Liebling, François Thierry M Marelli

Many applications rely on thermal imagers to complement or replace visible light sensors in difficult imaging conditions. Recent advances in machine learning have opened the possibility of analyzing or enhancing images, yet these methods require large anno ...

SPIE-INT SOC OPTICAL ENGINEERING2021

Aliasing mitigation in optical microscopy of dynamic biological samples by use of temporally modulated color illumination and a standard RGB camera

Michael Stefan Daniel Liebling, Christian Jaques

Significance: Despite recent developments in microscopy, temporal aliasing can arise when imaging dynamic samples. Modern sampling frameworks, such as generalized sampling, mitigate aliasing but require measurement of temporally overlapping and potentially ...

SPIE Society of Photo-optical Instrumentation Engineers2020

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Aditya Vardhan Varre, Nicolas Henri Bernard Flammarion, Loucas Pillaud-Vivien

Motivated by the recent successes of neural networks that have the ability to fit the data perfectly \emph{and} generalize well, we study the noiseless model in the fundamental least-squares setup. We assume that an optimum predictor fits perfectly inputs ...

Advances in Neural Information Processing Systems 20212021

Spatially-Variant CNN-Based Point Spread Function Estimation for Blind Deconvolution and Depth Estimation in Optical Microscopy

Michael Stefan Daniel Liebling, Adrian Shajkofci

Optical microscopy is an essential tool in biology and medicine. Imaging thin, yet non-flat objects in a single shot (without relying on more sophisticated sectioning setups) remains challenging as the shallow depth of field that comes with high-resolution ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Quality Evaluation Of Static Point Clouds Encoded Using MPEG Codecs

Touradj Ebrahimi, Evangelos Alexiou

This paper presents a quality evaluation study of point cloud codecs that have been recently standardised by the MPEG committee. In particular, a subjective experiment to assess their performance in terms of bitrate against visual quality is designed and r ...

IEEE2020