Publications associées à WebP

On Block Prediction For Learning-Based Point Cloud Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Evangelos Alexiou

Point clouds are among popular visual representations for immersive media. However, the vast amount of information generated during their acquisition requires effective compression for practical applications. Although relevant activities from standardizati ...

IEEE2021

Perceptual Quality Study On Deep Learning Based Image Compression

Touradj Ebrahimi, Pinar Akyazi

Recently deep learning based image compression has made rapid advances with promising results based on objective quality metrics. However, a rigorous subjective quality evaluation on such compression schemes have rarely been reported. This paper aims at pe ...

IEEE2019

Dynamic Adaptive Streaming for Multi-Viewpoint Omnidirectional Videos

Pascal Frossard, Francesca De Simone, Xavier Corbillon

Full immersion inside a Virtual Reality (VR) scene requires six Degrees of Freedom (6DoF) applications where the user is allowed to perform translational and rotational movements within the virtual space. The implementation of 6DoF applications is however ...

ASSOC COMPUTING MACHINERY2018

Caching of Bivariate Gaussians with Non-Uniform Preference Probabilities

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

Caching is technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. We study this method in a lossy source coding setting with Gaussian databases. A good caching strategy minimizes the data ...

2017

A Gaussian Source Coding Perspective on Caching and Total Correlation

Guillaume Jean Op 't Veld

Communication technology has advanced up to a point where children are getting unfamiliar with themost iconic symbol in IT: the loading icon. We no longer wait for something to come on TV, nor for a download to complete. All the content we desire is availa ...

EPFL2017

Compressive Multichannel Cortical Signal Recording

Pierre Vandergheynst, Alexandre Schmid, Mahsa Shoaran, Yusuf Leblebici, Mahdad Hosseini Kamal

This paper presents a novel approach to acquire multichannel wireless intracranial neural data based on a compressive sensing scheme. The designed circuits are extremely compact and low-power which confirms the relevance of the proposed approach for multic ...

IEEE2013

Dataflow Program Analysis and Refactoring Techniques for Design Space Exploration: MPEG-4 AVC/H.264 Decoder Implementation Case Study

Marco Mattavelli, Simone Casale Brunet, Claudio Paolo Alberti, Ab Al Hadi Bin Ab Rahman

This paper presents a methodology to perform design space exploration of complex signal processing systems implemented using the CAL dataflow language. In the course of space exploration, critical path in dataflow programs is first presented, and then anal ...

IEEE2013

Context-dependent JPEG backward-compatible high-dynamic range image compression

Touradj Ebrahimi

High Dynamic Range (HDR) imaging is expected, together with ultra-high definition (UHD) and high frame rate (HFR) video, to become a technology that may change photo, TV, and film industries. Many cameras and displays capable of capturing and rendering bot ...

2013

A JPEG backward-compatible HDR image compression

Touradj Ebrahimi

High Dynamic Range (HDR) imaging is expected to become one of the technologies that could shape next generation of consumer digital photography. Manufacturers are rolling out cameras and displays capable of capturing and rendering HDR images. The popularit ...

Spie-Int Soc Optical Engineering2012

Netscope: Practical Network Loss Tomography

Patrick Thiran, Aikaterini Argyraki, Xuan Hung Nguyen, Maciej Kurant, Denisa Gabriela Ghita

We present Netscope, a tomographic technique that infers the loss rates of network links from unicast end-to-end measurements. Netscope uses a novel combination of first- and second-order moments of end-to-end measurements to identify and characterize the ...

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