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Publications associées (24)

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

EPFL2024

Synchrotron-based phase-contrast micro-CT as a tool for understanding pulmonary vascular pathobiology and the 3-D microanatomy of alveolar capillary dysplasia

Goran Lovric

This study aimed to explore the value of synchrotron-based phase-contrast microcomputed tomography (micro-CT) in pulmonary vascular pathobiology. The microanatomy of the lung is complex with intricate branching patterns. Tissue sections are therefore diffi ...

AMER PHYSIOLOGICAL SOC2020

A combined on-the-fly/interpolation procedure for evaluating energy values needed in molecular simulations

Jiri Vanicek, Konstantin Karandashev

We propose an algorithm for molecular dynamics or Monte Carlo simulations that uses an interpolation procedure to estimate potential energy values from energies and gradients evaluated previously at points of a simplicial mesh. We chose an interpolation pr ...

2019

SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion

Jean-Philippe Thiran, Mohammad Saeed Rad

Despite well-established baselines, learning of scene depth and ego-motion from monocular video remains an ongoing challenge, specifically when handling scaling ambiguity issues and depth inconsistencies in image sequences. Much prior work uses either a su ...

IEEE COMPUTER SOC2019

An Adaptive Parameterization for Efficient Material Acquisition and Rendering

Wenzel Alban Jakob

One of the key ingredients of any physically based rendering system is a detailed specification characterizing the interaction of light and matter of all materials present in a scene, typically via the Bidirectional Reflectance Distribution Function (BRDF) ...

ASSOC COMPUTING MACHINERY2018

An Adaptive Parameterization for Efficient Material Acquisition and Rendering

Wenzel Alban Jakob

ASSOC COMPUTING MACHINERY2018

Busy Man’s Synthesis: Combinational Delay Optimization With SAT

Giovanni De Micheli, Mathias Soeken

Boolean SAT solving can be used to find a minimum- size logic network for a given small Boolean function. This paper extends the SAT formulation to find a minimum-size network under delay constraints. Delay constraints are given in terms of input arrival t ...

Ieee2017

Fast Segmentation from Blurred Data in 3D Fluorescence Microscopy

Michaël Unser, Martin Kurt Storath

We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model, which are capable of deali ...

2017

Limitations of patterning thin films by shadow mask high vacuum chemical vapor deposition

Patrik Willi Hoffmann, Yury Kuzminykh, Michael Oliver Reinke

A key factor in engineering integrated devices such as electro-optic switches or waveguides is the patterning of high quality crystalline thin films into specific geometries. In this contribution high vacuum chemical vapor deposition (HV-CVD) was employed ...

Elsevier2014

Appearance-based Active, Monocular, Dense Reconstruction for Micro Aerial Vehicle

Davide Scaramuzza

In this paper, we investigate the following problem: given the image of a scene, what is the trajectory that a robot-mounted camera should follow to allow optimal dense depth estimation? The solution we propose is based on maximizing the information gain o ...

2014

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