Concept

Anisotropic diffusion

Related publications (57)

A generic diffusion-based approach for 3D human pose prediction in the wild

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions. To address these challenges, we propose a diffusion-based approach th ...

IEEE2023

Maximum likelihood bolometry for ASDEX upgrade experiments

Riccardo Rossi

Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, h ...

Bristol2023

The effects of a spur dike location in a 90° sharp channel bend on flow field: Focus on anisotropy degree and anisotropy nature

Anton Schleiss

In this research, the flow features around a spur dike located in a 90˚ sharp channel bend have been studied experimentally in detail. Results showed that the effects of the spur dike on upstream sections increased by increasing α (spur dike location from ...

2023

Annihilation Filter Approach For Estimating Graph Dynamics From Diffusion Processes

Pascal Frossard, Arun Venkitaraman

We propose an approach for estimating graph diffusion processes using annihilation filters from a finite set of observations of the diffusion process made at regular intervals. Our approach is based on the key observation that a graph diffusion process can ...

IEEE2022

Image Denoising with Control over Deep Network Hallucination

Sabine Süsstrunk, Majed El Helou, Qiyuan Liang

Deep image denoisers achieve state-of-the-art results but with a hidden cost. As witnessed in recent literature, these deep networks are capable of overfitting their training distributions, causing inaccurate hallucinations to be added to the output and ge ...

Society for Imaging Science and Technology (IS&T)2022

Coarse graining and large-N behavior of the d-dimensional N-clock model

Matthias Ruf

We study the asymptotic behavior of the N-clock model, a nearest neighbors ferromagnetic spin model on the d-dimensional cubic epsilon-lattice in which the spin field is constrained to take values in a discretization S-N of the unit circle S-1 consisting o ...

2021

Image reconstruction method based on a trained non-linear mapping

Jean-Philippe Thiran, Dimitris Perdios, Marcel Arditi, Adrien Besson, Florian Martinez

The present invention concerns an array processing image reconstruction method comprising: receiving (13) a set of echo waveforms as measurements from the object of interest; defining (15) a measurement model linking an unknown image of the object to the m ...

2020

Simulation of silicon KOH and dry etching methods for micromould fabrication

Laurène Tribolet

The purpose of this project is to investigate the suitability of wet etching methods such as KOH etching for silicon micromoulds fabrication. Those moulds are intended for preceramic polymer (PCP) casting and specific requirements regarding the profile of ...

2020

Adaptive Regularization For Three-Dimensional Optical Diffraction Tomography

Michaël Unser, Demetri Psaltis, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ahmed Ayoub

Optical diffraction tomography (ODT) allows one to quantitatively measure the distribution of the refractive index of the sample. It relies on the resolution of an inverse scattering problem. Due to the limited range of views as well as optical aberrations ...

IEEE2020

Graph-based image representation learning

Renata Khasanova

Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...

EPFL2019

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