Publications de Pascal Frossard

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We consider streaming of pre-encoded and packetized media over best-effort networks in presence of acknowledgment feedbacks. We first review the rate-distortion optimization framework in such scenarios. Given an estimation of future transmission resources, and knowing about past transmissions and received acknowledgments, a scheduling algorithm is defined as a mechanism that selects the data to send over the network at any given time, so as to minimize the end-to-end distortion for the given communication r

We investigate methods for manipulating classifier explanations while keeping the predictions unchanged. Our focus is on using a sparse attack, which seeks to alter only a minimal number of input features. We present an efficient and novel algorithm for co ...

We address the problem of data gathering in adhoc networks. We propose a novel framework where sensor signals are quantized and mapped to a finite field. The network nodes then combine the data from different sensors to form messages that are transmitted t ...

In patients with stable Coronary Artery Disease (CAD), the identification of lesions which will be responsible of a myocardial infarction (MI) during follow-up remains a daily challenge. In this work, we propose to predict culprit stenosis by applying a de ...

This paper addresses the problem of image alignment based on random measurements. Image alignment consists of estimating the relative transformation between a query image and a reference image. We consider the specific problem where the query image is prov ...

This paper proposes a novel joint reconstruction algorithm to decode sets of correlated images from distributively compressed images. We consider a scenario where the images captured at different viewpoints are encoded independently using transform-based coding solutions (e.g., SPIHT) with a balanced rate distribution among different cameras. A central decoder jointly processes the compressed images and reconstructs an image pair by exploiting the correlation between images. The central decoder first estima

In this paper, we propose a novel design for network coding vectors that limits the overhead information. Network coding vectors contain information regarding the operations the packets have undergone in the network nodes. They are used at the decoder side ...

The spatial arrangement of cells is fundamental to their function, but single-cell RNA sequencing loses spatial context by dissociating cells from tissues. We present LUNA, a generative AI model that reassembles dissociated cells into tissue structures solely from gene expression by learning spatial priors from existing spatially resolved datasets. We apply and validate LUNA across multiple technologies including reconstructing the MERFISH whole mouse brain atlas with over 1.2 million cells, de novo reassem

Dynamic adaptive streaming addresses user heterogeneity by providing multiple encoded representations at different rates and/or resolutions for the same video content. For delay-sensitive applications, such as live streaming, there is however a stringent r ...

Multiview Video Coding (MVC) is a technique that permits efficient compression of multiview video. MVC uses variable block size motion and disparity estimation for block matching. This requires an exhaustive search process that involves all possible macro- ...

We investigate the problem of collaborative video streaming with Raptor network coding over overlay networks. We exploit path and source diversity, as well as basic processing capabilities of network nodes to increase the overall throughput and improve the ...

The construction of a meaningful graph plays a crucial role in the emerging field of signal processing on graphs. In this paper, we address the problem of learning graph Laplacians, which is similar to learning graph topologies, such that the input data fo ...

Deep networks have recently been shown to be vulnerable to universal perturbations: there exist very small image-agnostic perturbations that cause most natural images to be misclassified by such classifiers. In this paper, we provide a quantitative analysi ...

In this paper, we consider the problem of manifold approximation with affine subspaces. Our objective is to discover a set of low dimensional affine subspaces that represents manifold data accurately while preserving the manifold’s structure. For this purp ...

Due to their wide field of view, omnidirectional cameras are frequently used by autonomous vehicles, drones and robots for navigation and other computer vision tasks. The images captured by such cameras, are often analyzed and classified with techniques de ...

We propose a method to compute scale invariant features in omnidirectional images. We present a formulation based on Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that describe the mirror and lens structure in ...

In this paper we propose a method to adapt the quantization tables of typical block-based transform codecs when the input to the encoder is a panoramic image resulting from equirectangular projection of a spherical image. When the visual content is project ...

Network coding has recently emerged as an alternative to traditional routing algorithms in communication systems. In network coding, the network nodes can combine the packets they receive before forwarding them to the neighbouring nodes. Intensive research efforts have demonstrated that such a processing in the network nodes can provide advantages in terms of throughput or robustness. These potentials, combined with the advent of ad hoc and wireless delivery architectures have triggered the interest of rese

This paper addresses the problem of optimizing the playback delay experienced by a population of heterogeneous clients, in video streaming applications. We consider a typical broadcast scenario, where clients subscribe to different portions of a scalable v ...

In multiview video services, multiple cameras acquire the same scene from different perspectives, which results in correlated video streams. This generates large amounts of highly redundant data, which need to be properly handled during encoding and transm ...

Pascal Frossard

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The virtue of patience in low complexity scheduling of packetized media with feedback

Sparse Attacks for Manipulating Explanations in Deep Neural Network Models

Performance Bounds for Sensor Data Gathering by Coding in Finite Fields

Predicting future myocardial infarction from angiographies with deep learning

Optimal image alignment with random projections of manifolds: algorithm and geometric analysis

Joint Reconstruction of Correlated Images from Compressed Images

Toward one Symbol Network Coding Vectors

Tissue Reassembly with Generative AI

Delay-Power-Rate-Distortion Optimization of Video Representations for Dynamic Adaptive Streaming

Fast encoding techniques for Multiview Video Coding

Collaborative video streaming with Raptor network coding

Laplacian Matrix Learning for Smooth Graph Signal Representation

Robustness of Classifiers to Universal Perturbations: A Geometric Perspective

Linear Manifold Approximation based on Differences of Tangents

Geometry Aware Convolutional Filters for Omnidirectional Images Representation

Scale Invariant Features and Polar Descriptors in Omnidirectional Imaging

Geometry-driven quantization for omnidirectional image coding

Network coding: from theory to media streaming

Playback Delay and Buffering Optimization in Scalable Video Broadcasting

Packet Scheduling in Multicamera Capture Systems