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Art

Publications associées (68)

MATHICSE Technical Report : Mathematical Foundations of Adaptive Isogeometric Analysis

Annalisa Buffa, Rafael Vazquez Hernandez

This paper reviews the state of the art and discusses recent developments in the field of adaptive isogeometric analysis, with special focus on the mathematical theory. This includes an overview of available spline technologies for the local resolution of ...

EPFL2021

Learning Decoupled Representations for Human Pose Forecasting

Alexandre Massoud Alahi, Yuejiang Liu, Saeed Saadatnejad, Taylor Ferdinand Mordan, Behnam Parsaeifard

Human pose forecasting involves complex spatiotemporal interactions between body parts (e.g., arms, legs, spine). State-of-the-art approaches use Long Short-Term Memories (LSTMs) or Variational AutoEncoders (VAEs) to solve the problem. Yet, they do not eff ...

IEEE2021

Painting by Numbers: Computational Methods and the History of Art

Leonardo Laurence Impett

This thesis presents a new methodology for computational art history, in the tradition of Distant Reading from literary criticism. This method is based on operationalisation, the transcription of a concept or theory from cultural history into an algorithm. ...

EPFL2020

An Assessment of the State-of-the-Art from the 2019 ARO Dynamic Stall Workshop

Karen Ann J Mulleners, Fatma Ayancik Cinoglu

Dynamic stall has been a limiting factor in design and operation on rotating systems within the rotorcraft, propulsion, and sustainable energy disciplines for more than forty years, impacting operational performance and component fatigue. In the last decad ...

2020

RobustBench: a standardized adversarial robustness benchmark

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

Evaluation of adversarial robustness is often error-prone leading to overestimation of the true robustness of models. While adaptive attacks designed for a particular defense are a way out of this, there are only approximate guidelines on how to perform th ...

2020

The organisation of science: topics, incentives and funding.

Omar Ballester Gonzalez

Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well ...

EPFL2020

Multi-Modal Recurrent Attention Networks for Facial Expression Recognition

Seungryong Kim, Jiyoung Lee

Recent deep neural networks based methods have achieved state-of-the-art performance on various facial expression recognition tasks. Despite such progress, previous researches for facial expression recognition have mainly focused on analyzing color recordi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking

Pascal Fua, Andrii Maksai

Identity Switching remains one of the main difficulties Multiple Object Tracking (MOT) algorithms have to deal with. Many state-of-the-art approaches now use sequence models to solve this problem but their training can be affected by biases that decrease t ...

IEEE2019

Teaching Architecture - A dialogue

Inès Lamunière

What are the pressing questions in architecture – in teaching, research and practice? Based on their many years of experience, professors Inès Lamunière and Laurent Stalder come together in five meetings to search for answers. They describe an approach to ...

Birkhäuser2019

Recurrent U-Net for Resource-Constrained Segmentation

Pascal Fua, Mathieu Salzmann, Joachim Ludovic Hugonot, Wei Wang, Kaicheng Yu

State-of-the-art segmentation methods rely on very deep networks that are not always easy to train without very large training datasets and tend to be relatively slow to run on standard GPUs. In this paper, we introduce a novel recurrent U-Net architecture ...

IEEE COMPUTER SOC2019

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