Publications associées à Cinéma en relief

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Portfolio2023

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Zhuoqian Yang, Siyuan Li

We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photo-like images of fullbody humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in sy ...

Ieee Computer Soc2023

MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency

Mathieu Salzmann, Jiancheng Yang, Kun Sun, Yunhua Zhang

3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Inspired by the great success of cycle t ...

Ieee Computer Soc2023

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Pascal Fua, Pamuditha Udaranga Wickramasinghe, Patrick Moller Jensen, 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

Robust Isometric Non-Rigid Structure-From-Motion

Shaifali Parashar

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...

IEEE COMPUTER SOC2022

Using Animal Motion Capture to Learn Neural Representations

Semih Günel

Understanding behavior from neural activity is a fundamental goal in neuroscience. It has practical applications in building robust brain-machine interfaces, human-computer interaction, and assisting patients with neurological disabilities. Despite the eve ...

EPFL2022

Simultaneous 3D acquisition of H-1 MRF and Na-23 MRI

Tom Hilbert

Purpose To develop a 3D MR technique to simultaneously acquire proton multiparametric maps (T-1, T-2, and proton density) and sodium density weighted images over the whole brain. Methods We implemented a 3D stack-of-stars MR pulse sequence which consists o ...

WILEY2022

Deep eyes: Joint depth inference using monocular and binocular cues

Siyuan Li, Chen Zhang, Yang Yang

Human visual system relies on both monocular focusness cues and binocular stereo cues to gain effective 3D perception. Correspondingly, depth from focus/defocus (DfF/DfD) and stereo matching are two most studied passive depth sensing schemes, which are tra ...

ELSEVIER2021

Beyond Cameras: Real-Time High-Resolution 3D and Panoramic MultiView Vision Systems with Their Applications

Bilal Demir

The cameras are invented by imitating the human visual system to capture the scene. The camera technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid zoom has become standard features for smartphone flagships. In ...

EPFL2020

Proton-transfer-induced 3D/2D hybrid perovskites suppress ion migration and reduce luminance overshoot

Mohammad Khaja Nazeeruddin, Emad Oveisi, Hobeom Kim

Perovskite light-emitting diodes (PeLEDs) based on three-dimensional (3D) polycrystalline perovskites suffer from ion migration, which causes overshoot of luminance over time during operation and reduces its operational lifetime. Here, we demonstrate 3D/2D ...

Nature Research2020

XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera

Pascal Fua, Helge Jochen Rhodin, Gerard Pons Moll

We present a real-time approach for multi-person 3D motion capture at over 30 fps using a single RGB camera. It operates successfully in generic scenes which may contain occlusions by objects and by other people. Our method operates in subsequent stages. T ...

2020

Mo(2)Cap(2): Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera

Pascal Fua, Helge Jochen Rhodin

We propose the first real-time system for the egocentric estimation of 3D human body pose in a wide range of unconstrained everyday activities. This setting has a unique set of challenges, such as mobility of the hardware setup, and robustness to long capt ...

2019

Crystal Orientation Drives the Interface Physics at Two/Three-Dimensional Hybrid Perovskites

Jacques-Edouard Moser, Mohammad Khaja Nazeeruddin, Sanghyun Paek, Giulia Grancini, Kyung Taek Cho, Cristina Roldán Carmona, Valentin Ianis Emmanuel Queloz, Marine Eva Fedora Bouduban

Combining halide perovskites with tailored dimensionality into two/three-dimensional (2D/3D) systems has revealed a powerful strategy to boost the performances of perovskite photovoltaics (PVs). Despite recent advances, a clear understanding of the intimat ...

2019

Neural Scene Decomposition for Multi-Person Motion Capture

Pascal Fua, Mathieu Salzmann, Isinsu Katircioglu, Helge Jochen Rhodin, Victor Constantin

Learning general image representations has proven key to the success of many computer vision tasks. For example, many approaches to image understanding problems rely on deep networks that were initially trained on ImageNet, mostly because the learned featu ...

IEEE2019

3-Dimensional Ultrasound Imaging for Medical Telesonography: Algorithms and Architectures

Aya Mohamed Naguib Ahmed Ibrahim

Enabling telemedicine in Ultrasound (US) imaging, i.e. telesonography, is until today just a wish. Although US has incomparable advantages such as safety in use, lower cost and complexity, and capability to be utilized in many applications, it is limited i ...

EPFL2018

NeuroMorph: A Software Toolset for 3D Analysis of Neurite Morphology and Connectivity

Graham Knott, Jérôme Blanc, Anne Alison Jorstad

The geometries of axons, dendrites and their synaptic connections provide important information about their functional properties. These can be collected directly from measurements made on serial electron microscopy images. However, manual and automated se ...

2018

LF-Net: Learning Local Features from Images

Pascal Fua, Kwang Moo Yi, Eduard Trulls Fortuny, Yuki Ono

We present a novel deep architecture and a training strategy to learn a local feature pipeline from scratch, using collections of images without the need for human supervision. To do so we exploit depth and relative camera pose cues to create a virtual tar ...

2018

Charge Neutralization and Direct Thrust Measurements from Bipolar Pairs of Ionic- Electrospray Thrusters

Herbert Shea, Daniel George Courtney

lectrospray (ES) thrusters are unique in their ability to emit both positive and negative beams, each contributing similarly to thrust. Spacecraft charging could be prevented without a dedicated neutralizer if currents of simultaneously emitted opposing po ...

2017

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

Single-FPGA 3D Ultrasound Beamformer

Jean-Philippe Thiran, Giovanni De Micheli, Federico Angiolini, Marcel Arditi, Aya Mohamed Naguib Ahmed Ibrahim, Ahmet Caner Yüzügüler

In medical diagnosis, ultrasound (US) imaging is one of the most common, safe, and powerful techniques. Volumetric (3D) US imaging, an emerging technique, is even more attractive than standard 2D imaging, as it allows for imaging without the local presence ...

Ieee2016