Publications associées à Deep Non-Rigid Structure-From-Motion: A Sequence-to-Sequence Translation Perspective

Publications associées (20)

Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing

Self-supervised learning through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) image representation learning, and thus embodies a significant potential for content-based image retrieval (CBIR) from ever-growing R ...

2024

Machine learning-based prediction of fish acute mortality: implementation, interpretation, and regulatory relevance

Fernando Perez Cruz

Regulation of chemicals requires knowledge of their toxicological effects on a large number of species, which has traditionally been acquired through in vivo testing. The recent effort to find alternatives based on machine learning, however, has not focuse ...

2024

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

Yumeng Hou

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

Association for Computing Machinery2023

Relative stability toward diffeomorphisms indicates performance in deep nets

Matthieu Wyart, Mario Geiger, Leonardo Petrini, Alessandro Favero

Understanding why deep nets can classify data in large dimensions remains a challenge. It has been proposed that they do so by becoming stable to diffeomorphisms, yet existing empirical measurements support that it is often not the case. We revisit this qu ...

IOP Publishing Ltd2022

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

Many image-based perception tasks can be formulated as detecting, associating and tracking semantic keypoints, e.g., human body pose estimation and tracking. In this work, we present a general framework that jointly detects and forms spatio-temporal keypoi ...

IEEE Institute of Electrical and Electronics Engineers2022

On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation

Pascal Fua, Sina Honari, Leonardo Citraro, Soumava Kumar Roy

Supervised approaches to 3D pose estimation from single images are remarkably effective when labeled data is abundant. However, as the acquisition of ground-truth 3D labels is labor intensive and time consuming, recent attention has shifted towards semi- a ...

IEEE2022

Multi-fidelity surrogate modeling using long short-term memory networks

Jan Sickmann Hesthaven

When evaluating quantities of interest that depend on the solutions to differential equations, we inevitably face the trade-off between accuracy and efficiency. Especially for parametrized, time-dependent problems in engineering computations, it is often t ...

ELSEVIER SCIENCE SA2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

Vasiliki Tileli, Reinis Ignatans

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switch ...

WILEY-V C H VERLAG GMBH2022

Urban Data: Sources and Targeted Applications for Urban Planning Indicators Modelling

Jérôme Chenal

Urban data strongly favored by urban digitization and web 2.0 constitute the raw material whose sources often diverge. However, as far as we know, little or no work has been done to explore the sources and targeted applications for urban planning indicator ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Generative Adversarial Networks for Localized Vibrotactile Feedback in Haptic Surfaces

Yves Perriard, Paolo Germano, Adrien Jean-Michel Thabuis, Jonathan André Jean-Marie Chavanne, Xiaotao Ren, Camilo Hernandez Mejia

Touch-screens are the most relevant interface in the context of human-computer interaction. Moreover, they are widely used as interaction means for digital musical instruments, where a complex action-perception loop is involved in the user experience. This ...

IEEE2021

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

Berend Smit, Seyedmohamad Moosavi, Daniele Ongari, Kevin Maik Jablonka

By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal–organic frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges. We simply have too many ma ...

2020

Resting-state EEG topographies: Reliable and sensitive signatures of unilateral spatial neglect

Dimitri Nestor Alice Van De Ville, Elvira Pirondini

Theoretical advances in the neurosciences are leading to the development of an increasing number of proposed interventions for the enhancement of functional recovery after brain damage. Integration of these novel approaches in clinical practice depends on ...

2020

Design and control of a prototype structure that adapts to loading through large shape changes

Ian Smith, Gennaro Senatore, Arka Prabhata Reksowardojo

This paper reports on experimental testing that was carried out on a prototype adaptive structure designed to counteract the effect of loading through controlled large shape changes. The prototype is 6.6 m truss equipped with 12 linear actuators which has ...

ELSEVIER2020

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

Deep Spline Networks With Control Of Lipschitz Regularity

Michaël Unser, Shayan Aziznejad

The motivation for this work is to improve the performance of deep neural networks through the optimization of the individual activation functions. Since the latter results in an infinite-dimensional optimization problem, we resolve the ambiguity by search ...

IEEE2019

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Frank Grégoire Jean de Morsier

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

EPFL2014

Energy-aware adaptive bi-Lipschitz embeddings

Volkan Cevher, Bubacarr Bah

We propose a dimensionality reducing matrix design based on training data with constraints on its Frobenius norm and number of rows. Our design criteria is aimed at preserving the distances between the data points in the dimensionality reduced space as muc ...

2013

Beyond Bits: Reconstructing Images from Local Binary Descriptors

Pierre Vandergheynst, Alexandre Massoud Alahi, Emmanuel D'Angelo

Local Binary Descriptors (LBDs) are good at matching image parts, but how much information is actually carried? Surprisingly, this question is usually ignored and replaced by a comparison of matching performances. In this paper, we directly address it by t ...

2012

Lightweight Modular Staging: A Pragmatic Approach to Runtime Code Generation and Compiled DSLs

Martin Odersky, Tiark Rompf

Good software engineering practice demands generalization and abstraction, whereas high performance demands specialization and concretization. These goals are at odds, and compilers can only rarely translate expressive high-level programs to modern hardwar ...

2012

Training Distributed Neural Networks by Consensus

Martin Hasler, Leonidas Georgopoulos

We address the problem of learning a classifier from distributed data over a number of arbitrarily connected machines without exchange of the datapoints. Our purpose is to train a neural network at each machine as if the entire dataset was locally availabl ...

2011