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Keyword-based Image Color Re-rendering with Semantic Segmentation

Publications associées (35)

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SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

Jean-Philippe Thiran, Hazim Kemal Ekenel, Mohammad Saeed Rad

By benefiting from perceptual losses, recent studies have improved significantly the performance of the super-resolution task, where a high-resolution image is resolved from its low-resolution counterpart. Although such objective functions generate near-ph ...

IEEE COMPUTER SOC2019

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

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...

EPFL2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Sciences et Techniques de l’Ingénieur (STI)2017

Efficient Transductive Semantic Segmentation

Mathieu Salzmann

Semantically describing the contents of images is one of the classical problems of computer vision. With huge numbers of images being made available daily, there is increasing interest in methods for semantic pixel labelling that exploit large image sets. ...

Ieee2016

Fast and Robust Segmentation of the Striatum Using Deep Convolutional Neural Networks

Kyong Hwan Jin

Background: Automated segmentation of brain structures is an important task in structural and functional image analysis. We developed a fast and accurate method for the striatum segmentation using deep convolutional neural networks (CNN). New method: T1 ma ...

Elsevier2016

Multilingual Visual Sentiment Concept Matching

Nikolaos Pappas, Hongyi Liu

What would someone from another culture think of this photograph I just took? Would they think my picture of this 'wilted flower' was also sentimentally positive or would they perceive it negatively instead? Or what if I wanted to find other photographs th ...

Assoc Computing Machinery2016

Semantic-Improved Color Imaging Applications: It Is All About Context

Sabine Süsstrunk, Albrecht Johannes Lindner

Abstract—Multimedia data with associated semantics is omnipresent in today’s social online platforms in the form of keywords, user comments and so forth. This article presents a statistical framework designed to infer knowledge in the imaging domain from t ...

2015

Image processing on reconfigurable hardware for continuous monitoring of fluorescent biomarkers in cell cultures

Julien Michel Ghaye

Fluorescence microscopy is a widespread tool in biological research. It is the primary modality for bioimaging and empowers the study and analysis of multitudes of biological processes. It can be applied to fixed biosamples, that is samples with frozen bio ...

EPFL2015

Saliency-based representations and multi-component classifiers for visual scene recognition

Marco Fornoni

Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...

EPFL2014