Publications by Pascal Frossard

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Sparse molecular image representation

Pascal Frossard, Sofia Karygianni

Sparsity-based models have proven to be very effective in most image processing applications. The notion of sparsity has recently been extended to structured sparsity models where not only the number of components but also their support is important. This ...

Elsevier2016

Reference view selection in DIBR-based multiview coding

Pascal Frossard, Thomas Maugey

Augmented reality, interactive navigation in 3D scenes, multiview video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant in ...

Institute of Electrical and Electronics Engineers2016

Robustness of classifiers: from adversarial to random noise

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

Several recent works have shown that state-of-the-art classifiers are vulnerable to worst-case (i.e., adversarial) perturbations of the datapoints. On the other hand, it has been empirically observed that these same classifiers are relatively robust to ran ...

2016

Complexity Constrained Representation Selection for Dynamic Adaptive Streaming

Pascal Frossard, Laura Toni, Chenglin Li

In this paper, we propose a representation selection optimization problem for complexity constrained adaptive video streaming that properly takes into account the different complexity-rate-distortion (C-R-D) characteristics of the videos when implementing ...

Ieee2016

Graph-based compression of dynamic 3D point cloud sequences

Pascal Frossard

This paper addresses the problem of compression of 3D point cloud sequences that are characterized by moving 3D positions and color attributes. As temporally successive point cloud frames are similar, motion estimation is key to effective compression of th ...

Institute of Electrical and Electronics Engineers2016

Structured Dimensionality Reduction for Additive Model Regression

Pascal Frossard, Alhussein Fawzi

Additive models are regression methods which model the response variable as the sum of univariate transfer functions of the input variables. Key benefits of additive models are their accuracy and interpretability on many real-world tasks. Additive models a ...

Institute of Electrical and Electronics Engineers2016

In-Network View Synthesis for Interactive Multiview Video Systems

Pascal Frossard, Laura Toni

In multiview applications, camera views can be used as reference views to synthesize additional virtual viewpoints, allowing users to freely navigate within a 3D scene. However, bandwidth constraints may restrict the number of reference views sent to clien ...

Ieee-Inst Electrical Electronics Engineers Inc2016

DeepFool: a simple and accurate method to fool deep neural networks

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

State-of-the-art deep neural networks have achieved impressive results on many image classification tasks. However, these same architectures have been shown to be unstable to small, well sought, perturbations of the images. Despite the importance of this p ...

2016

Adaptive data augmentation for image classification

Pascal Frossard, Alhussein Fawzi

Data augmentation is the process of generating samples by transforming training data, with the target of improving the accuracy and robustness of classifiers. In this paper, we propose a new automatic and adaptive algorithm for choosing the transformations ...

IEEE2016

Pascal Frossard

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Sparse molecular image representation

Reference view selection in DIBR-based multiview coding

Robustness of classifiers: from adversarial to random noise

Distributed wireless video caching placement for dynamic adaptive streaming

Complexity Constrained Representation Selection for Dynamic Adaptive Streaming

Graph-based compression of dynamic 3D point cloud sequences

Structured Dimensionality Reduction for Additive Model Regression

In-Network View Synthesis for Interactive Multiview Video Systems

DeepFool: a simple and accurate method to fool deep neural networks

Adaptive data augmentation for image classification

Reference view selection in DIBR-based multiview coding

Sparse molecular image representation

Distributed wireless video caching placement for dynamic adaptive streaming

Complexity Constrained Representation Selection for Dynamic Adaptive Streaming

In-Network View Synthesis for Interactive Multiview Video Systems

Graph-based compression of dynamic 3D point cloud sequences

Adaptive data augmentation for image classification

Robustness of classifiers: from adversarial to random noise

Structured Dimensionality Reduction for Additive Model Regression

DeepFool: a simple and accurate method to fool deep neural networks