Publications de Pascal Frossard

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Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have, however, large requirements in terms of both network and computational resources ...

Multiview plus depth (MVD) is an emerging video format with many applications, including 3-D television and free viewpoint television. During the broadcast of a compressed MVD video, transmission errors may cause the loss of whole frames, resulting in sign ...

This paper tackles low delay adaptive video streaming over error-prone networks. Our framework consists of an encoding station, an edge server and a set of clients with various access rates. The edge server is capable of performing simple error concealment operations on the incoming data before forwarding the adapted media to its clients. We study two encoding scenarios: versions (multiple encodings at various output rates) and layers. We develop a unified end-to-end distortion model, which we use to derive

This paper presents a new, highly flexible, scalable image coder based on a Matching Pursuit expansion. The dictionary of atoms is built by translation, rotation and anisotropic refinement of gaussian functions, in order to efficiently capture edges in natural images. In the same time, the dictionary is invariant under isotropic scaling, which interestingly leads to very simple spatial resizing operations. It is shown that the proposed scheme compares to state-of-the-art coders when the compressed image is

We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-supervised learning where all unlabelled examples belong to the same unknown cla ...

Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and inexpensive comparison metrics. In this work we introduce the filter graph dis ...

Deep neural networks have recently achieved tremendous success in image classification. Recent studies have however shown that they are easily misled into incorrect classification decisions by adversarial examples. Adversaries can even craft attacks by que ...

We investigate the problem of collaborative video streaming in overlay networks. We exploit path and source diversity, as well as basic processing capabilities of network nodes in order to increase the overall throughput and improve the video quality at th ...

We propose a preliminary investigation on the benefits and limitations of classifiers based on sparse representations. We specifically focus on the union of subspaces data model and examine binary classifiers built on a sparse non linear mapping (in a redu ...

This paper addresses the problem of the distributed delivery of correlated data sources with help of network coding. Network coding provides an alternative to routing algorithms and offers improved system performance, robustness and throughput, with no nee ...

This paper explores self-supervised disentangled representation learning within sequential data, focusing on separating time-indep- endent and time-varying factors in videos. We propose a new model that breaks the usual independence assumption between thos ...

Network data appears in very diverse applications, like biological, social, or sensor networks. Clustering of network nodes into categories or communities has thus become a very common task in machine learning and data mining. Network data comes with some ...

The concept of simultaneous source has recently become of interest in seismic exploration, due to its efficient or economic acquisition or both. The blended data overlapped between shot records are acquired in simultaneous source acquisition. Separating th ...

While every network node only relays messages in a traditional communication system, the recent network coding (NC) paradigm proposes to implement simple in-network processing with packet combinations in the nodes. NC extends the concept of "encoding" a me ...

To be efficient, data protection algorithms should generally exploit the properties of the media information in the transform domain. In this paper, we will advocate the use of non-linear image approximations using highly redundant dictionaries, for security algorithms. We show that a flexible image representation based on a multidimensional and geometry-based coding scheme, has precious attributes for security information embedding. Redundant expansions provide very good approximation properties, as well a

Important insights towards the explainability of neural networks reside in the characteristics of their decision boundaries. In this work, we borrow tools from the field of adversarial robustness, and propose a new perspective that relates dataset features ...

In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Ro ...

Deep neural network (DNN) inference tasks are computationally expensive. Digital DNN accelerators offer better density and energy efficiency than general-purpose processors but still not sufficient to be deployable on resource-constrained settings.Analog c ...

Morphology and spatial organisation provide complementary readouts of cellular state. However, reconstructing continuous cellular state landscapes from imaging data remains challenging, particularly in dense biological cultures. Here we present SI-SimCLR, a spatially informed self-supervised learning framework that learns biologically informative representations directly from fluorescence microscopy images without requiring segmentation or manual annotation. Combined with a graph-based partial optimal trans

New breakthroughs in image coding possibly rely in signal decomposition through non-separable basis functions. The work proposed in this paper provides an adaptive way of representing images as a sum of two-dimensional features. It presents a low bit-rate ...

Pascal Frossard

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Distributed Rate Allocation in Switch-Based Multiparty Videoconferencing System

Temporal and Inter-view Consistent Error Concealment Technique for Multiview plus Depth Video Broadcasting

Adaptive video streaming in lossy networks: versions or layers?

High flexibility scalable image coding

Graph-based classification of multiple observation sets

fGOT: Graph Distances Based on Filters and Optimal Transport

A Geometry-Inspired Decision-Based Attack

Network coding of rateless video in streaming overlays

Classification of unions of subspaces with sparse representations

Transmission of Correlated Information Sources with Network Coding

Sequential Representation Learning via Static-Dynamic Conditional Disentanglement

OrthoNet: Multilayer Network Data Clustering

Seismic Simultaneous Source Separation via Patchwise Sparse Representation

Network Coding Meets Multimedia: A Review

Redundant Image Representations in Security Applications

Hold me tight! Influence of discriminative features on deep network boundaries

Decoding the Interactions and Functions of Non-coding Rna with Artificial Intelligence

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Topology-aware reconstruction of cellular state landscapes from microscopy using self-supervised learning

Low rate and flexible image coding with redundant representations