Publications related to Low rate and flexible image coding with redundant representations

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Michela Testolina

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

Springer2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Daniel Kressner, Alice Cortinovis

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

Siam Publications2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

2023

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Bowen Huang

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS ...

2023

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Michela Testolina

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

2023

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

Touradj Ebrahimi, Vlad Hosu, Davi Nachtigall Lazzarotto, Michela Testolina

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

2023

Evaluating the effect of sparse convolutions on point cloud compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

2023

Communication-efficient distributed training of machine learning models

Thijs Vogels

In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...

EPFL2023

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Yunus Inan

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

EPFL2023

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

Michaël Unser, Rahul Parhi

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

IEEE Institute of Electrical and Electronics Engineers2023

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Michaël Unser

We propose an image-based elastography method to measure the heterogeneous stiffness inside a cell and its nucleus. It uses a widely accessible setup consisting of plate compression imaged with fluorescence microscopy. Our framework recovers a spatial map ...

IEEE2023

Shafranov shift correction to the Furth-Yoshikawa scaling of tokamak adiabatic compression

Olivier Sauter

In 1970, Furth and Yoshikawa (1970 Phys. Fluids 13 2593-6) introduced the scalings of adiabatic plasma compression. Basically, if the shape of the external plasma boundary and the aspect ratio are preserved during the compression, then the density, kinetic ...

2023

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Mohammad Ali Shaeri

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Gionata Ghiggi, Anne-Claire Marie Billault--Roux

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Jean-Philippe Thiran, Roser Vinals Terres

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

2023

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

Touradj Ebrahimi, Yuhang Lu

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

2023