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Learning Separable Filters

Publications associées (40)

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Perspectives on Individual Animal Identification from Biology and Computer Vision

Alexander Mathis, Maxime Michel André Vidal

Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current a ...

OXFORD UNIV PRESS INC2021

Beyond Cameras: Real-Time High-Resolution 3D and Panoramic MultiView Vision Systems with Their Applications

Bilal Demir

The cameras are invented by imitating the human visual system to capture the scene. The camera technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid zoom has become standard features for smartphone flagships. In ...

EPFL2020

Foreword to the Special Issue on Computer Vision-Based Approaches for Earth Observation

Devis Tuia

The five papers in this special section focus on computer vision-based approaches for Earth observation. These papers followed a series of events promoting works at the interface between computer vision and remote sensing: the special sessions organized at ...

2020

Painting by Numbers: Computational Methods and the History of Art

Leonardo Laurence Impett

This thesis presents a new methodology for computational art history, in the tradition of Distant Reading from literary criticism. This method is based on operationalisation, the transcription of a concept or theory from cultural history into an algorithm. ...

EPFL2020

Learning to Reduce Annotation Load

Ksenia Konyushkova

Modern machine learning methods and their applications in computer vision are known to crave for large amounts of training data to reach their full potential. Because training data is mostly obtained through humans who manually label samples, it induces a ...

EPFL2019

Variational Methods for Human Modeling

Timur Bagautdinov

A large part of computer vision research is devoted to building models and algorithms aimed at understanding human appearance and behaviour from images and videos. Ultimately, we want to build automated systems that are at least as capable as people when i ...

EPFL2018

Mean-Field methods for Structured Deep-Learning in Computer Vision

Pierre Bruno Baqué

In recent years, Machine Learning based Computer Vision techniques made impressive progress. These algorithms proved particularly efficient for image classification or detection of isolated objects. From a probabilistic perspective, these methods can predi ...

EPFL2018

Learning embeddings: efficient algorithms and applications

Cijo Jose

Learning to embed data into a space where similar points are together and dissimilar points are far apart is a challenging machine learning problem. In this dissertation we study two learning scenarios that arise in the context of learning embeddings and o ...

EPFL2018

Learning embeddings: efficient algorithms and applications

Cijo Jose

École Polytechnique Fédérale de Lausanne2018

Learning Robust Features and Latent Representations for Single View 3D Pose Estimation of Humans and Objects

Bugra Tekin

Estimating the 3D poses of rigid and articulated bodies is one of the fundamental problems of Computer Vision. It has a broad range of applications including augmented reality, surveillance, animation and human-computer interaction. Despite the ever-growin ...

EPFL2018