Publications associées à Beyond the Pixel-Wise Loss for Topology-Aware Delineation

Learning curves for the multi-class teacher-student perceptron

Elisabetta Cornacchia, Francesca Mignacco, Lenka Zdeborová, Bruno Loureiro, Bruno Loureiro

One of the most classical results in high-dimensional learning theory provides a closed-form expression for the generalisation error of binary classification with a single-layer teacher-student perceptron on i.i.d. Gaussian inputs. Both Bayes-optimal (BO) ...

IOP Publishing Ltd2023

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Ali Garjani

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

IEEE COMPUTER SOC2023

Deep Visual Re-Identification with Confidence

Alexandre Massoud Alahi, George Adaimi, Sven Kreiss

Transportation systems often rely on understanding the flow of vehicles or pedestrian. From traffic monitoring at the city scale, to commuters in train terminals, recent progress in sensing technology make it possible to use cameras to better understand th ...

2019

Low-rank and sparse subspace modeling of speech for DNN based acoustic modeling

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

Towards the goal of improving acoustic modeling for automatic speech recognition (ASR), this work investigates the modeling of senone subspaces in deep neural network (DNN) posteriors using low-rank and sparse modeling approaches. While DNN posteriors are ...

ELSEVIER SCIENCE BV2019

Perceptual Information Loss due to Impaired Speech Production

Hervé Bourlard, Afsaneh Asaei, Milos Cernak

Phonological classes define articulatory-free and articulatory-bound phone attributes. Deep neural network is used to estimate the probability of phonological classes from the speech signal. In theory, a unique combination of phone attributes form a phonem ...

2017

Sparse projections onto the simplex

Volkan Cevher, Anastasios Kyrillidis, Christoph Koch

Most learning methods with rank or sparsity constraints use convex relaxations, which lead to optimization with the nuclear norm or the`1-norm. However, several important learning applications cannot benet from this approach as they feature these convex no ...

JMLR W&CP2013

Distributed Compressed Representation of Correlated Image Sets

Vijayaraghavan Thirumalai

Vision sensor networks and video cameras find widespread usage in several applications that rely on effective representation of scenes or analysis of 3D information. These systems usually acquire multiple images of the same 3D scene from different viewpoin ...

EPFL2012

Image Reconstruction from Compressed Linear Measurements with Side Information

Pascal Frossard, Vijayaraghavan Thirumalai

This paper proposes a joint reconstruction algorithm for compressed correlated images that are given under the form of linear measurements. We consider the particular problem where one image is selected as the reference image and it is used as the side inf ...

2011

Joint reconstruction of correlated images from compressed linear measurements

Pascal Frossard, Vijayaraghavan Thirumalai

This paper proposes a joint reconstruction algorithm for compressed correlated images that are given under the form of linear measurements. We first propose a geometry based model in order to describe the correlation between visual information in pairs of ...

2010

Flexible Motion-Adaptive Video Coding with Redundant Expansions

Pascal Frossard, Pierre Vandergheynst, Adel Rahmoune

This paper presents a highly flexible video coding scheme (MP3D), based on the use of a redundant 3-D spatio-temporal dictionary of functions. Directionality and anisotropic scaling are key ingredients to the spatial components, that form a rich collection ...

2006

Progressive Coding of 3-D Objects Based on Overcomplete Decompositions

Pascal Frossard, Pierre Vandergheynst, Ivana Tosic

This paper presents a progressive coding scheme for 3-D objects, based on overcomplete signal expansions on the 2-D sphere. Due to increased freedom in the basis construction, redundant expansions have shown interesting approximation properties in the deco ...

2006