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Concept

Rendu volumique direct

Publications associées (30)

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Seyed Mohammad Mahdi Johari

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

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Martin Weigert

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Nature Portfolio2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Jiancheng Yang, Amos Sironi, Jian Yang

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...

Nature Publishing Group2023

Three-dimensional micro-CT images of UV-frozen flow fronts recorded at different flow regimes

Véronique Michaud, Jacobus Gerardus Rudolph Staal

Segmented micro-CT images of flow fronts produced by UV-flow freezing. Front morphologies correspond to capilary-dominated, equilibrated and viscous-dominated flow regimes. ...

Zenodo2023

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022

Sub-micrometer morphology of human atherosclerotic plaque revealed by synchrotron radiation-based mu CT-A comparison with histology

Goran Lovric, Anne Bonnin

Histology is a long standing and well-established gold standard for pathological characterizations. In recent years however, synchrotron radiation-based micro-computed tomography (SR mu CT) has become a tool for extending the imaging of two-dimensional thi ...

PUBLIC LIBRARY SCIENCE2022

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Pascal Fua, Pamuditha Udaranga Wickramasinghe, Mian Akbar Shah

There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

Springer2022

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Guillaume Marc Georges Vray, Devavrat Tomar

As distribution shifts are inescapable in realistic clinical scenarios due to inconsistencies in imaging protocols, scanner vendors, and across different centers, well-trained deep models incur a domain generalization problem in unseen environments. Despit ...

PMLR2022

Object Priors for Volumetric Image Segmentation

Pamuditha Udaranga Wickramasinghe

Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

EPFL2022

Differentiable Physically Based Rendering: Algorithms, Systems and Applications

Merlin Eléazar Nimier-David

Physically based rendering methods can create photorealistic images by simulating the propagation and interaction of light in a virtual scene. Given a scene description including the shape of objects, participating media, material properties, etc., the sim ...

EPFL2022

Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation

Alcherio Martinoli, Chiara Ercolani, Lixuan Tang

Chemical gas dispersion can represent a severe threat to human and animal lives, as well as to the environment. Constructing a map of the distribution of gas in a fast and reliable manner is critical to ensure accurate monitoring of at-risk facilities and ...

2022

The new X-ray/visible microscopy MAXWELL technique for fast three-dimensional nanoimaging with isotropic resolution

Giorgio Margaritondo, Lin Yang

Microscopy by Achromatic X-rays With Emission of Laminar Light (MAXWELL) is a new X-ray/visible technique with attractive characteristics including isotropic resolution in all directions, large-volume imaging and high throughput. An ultrathin, laminar X-ra ...

Nature Portfolio2022

Bragg edge tomography characterization of additively manufactured 316L steel

Roland Logé, Christian Leinenbach, Nikola Kalentics

In this work we perform a neutron Bragg edge tomography of stainless steel 316L additive manufacturing samples, one as built via standard laser powder bed fusion, and one using the novel three-dimensional (3D) laser shock peening technique. First, we consi ...

AMER PHYSICAL SOC2022

Perceptual Quality of Point Clouds with application to Compression

Evangelos Alexiou

Modern information technologies and human-centric communication systems employ advanced content representations for richer portrayals of the real world. The newly adopted imaging modalities offer additional information cues and permit the depiction of real ...

EPFL2021

Path Replay Backpropagation: Differentiating Light Paths using Constant Memory and Linear Time

Wenzel Alban Jakob, Delio Aleardo Vicini, Sébastien Nicolas Speierer

Differentiable physically-based rendering has become an indispensable tool for solving inverse problems involving light. Most applications in this area jointly optimize a large set of scene parameters to minimize an objective function, in which case revers ...

ASSOC COMPUTING MACHINERY2021

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Wenzel Alban Jakob, Delio Aleardo Vicini

We introduce a novel transmittance model to improve the volumetric representation of 3D scenes. The model can represent opaque surfaces in the volumetric light transport framework. Volumetric representations are useful for complex scenes, and become increa ...

ASSOC COMPUTING MACHINERY2021

2d-3d sculpture paintings

Sabine Süsstrunk, Roger Hersch, Mahmut Sami Arpa

We disclose a method for synthesizing by computer an artwork where 2D and 3D contents are integrated within a same composition. Such an artwork creates plausible effects for the viewers by showing a different relationship between 2D and 3D at each viewing ...

2020

Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data

Pascal Fua, Graham Knott, Edoardo Remelli, Pamuditha Udaranga Wickramasinghe

CNN-based volumetric methods that label individual voxels now dominate the field of biomedical segmentation. However, 3D surface representations are often required for proper analysis. They can be obtained by post-processing the labeled volumes which typic ...

2020

Radiative Backpropagation: An Adjoint Method for Lightning-Fast Differentiable Rendering

Wenzel Alban Jakob, Merlin Eléazar Nimier-David, Sébastien Nicolas Speierer

Physically based differentiable rendering has recently evolved into a powerful tool for solving inverse problems involving light. Methods in this area perform a differentiable simulation of the physical process of light transport and scattering to estimate ...

ASSOC COMPUTING MACHINERY2020