Publications related to Saliency Detection for Content-aware Image Resizing

Related publications (12)

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

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

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

Robust 3D Object Pose Estimation and Tracking from Monocular Images in Industrial Environments

Alberto Crivellaro

Recent advances in Computer Vision are changing our way of living and enabling new applications for both leisure and professional use. Regrettably, in many industrial domains the spread of state-of-the-art technologies is made challenging by the abundance ...

EPFL2016

Multiscale Centerline Extraction Based on Regression and Projection onto the Set of Elongated Structures

Amos Sironi

Automatically extracting linear structures from images is a fundamental low-level vision problem with numerous applications in different domains. Centerline detection and radial estimation are the first crucial steps in most Computer Vision pipelines aimin ...

EPFL2016

FASA: Fast, Accurate, and Size-Aware Salient Object Detection

Sabine Süsstrunk, Gökhan Yildirim

Fast and accurate salient-object detectors are important for various image processing and computer vision applications, such as adaptive compression and object segmentation. It is also desirable to have a detector that is aware of the position and the size ...

Springer-Verlag Berlin2015

Are All Pixels Equally Important? Towards Multi-Level Salient Object Detection

Gökhan Yildirim

When we look at our environment, we primarily pay attention to visually distinctive objects. We refer to these objects as visually important or salient. Our visual system dedicates most of its processing resources to analyzing these salient objects. An ana ...

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

A Fast Parts-based Approach to Speaker Verification using Boosted Slice Classifiers

Sébastien Marcel, Mathew Magimai Doss, Anindya Roy

Speaker verification on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, possibl ...

2012

FREAK: Fast Retina Keypoint

Pierre Vandergheynst, Alexandre Massoud Alahi, Raphaël Ortiz

A large number of vision applications rely on matching keypoints across images. The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: Scale Invariant Feature Transform (SIFT), Speed-up Robust Feature (SU ...

Ieee2012

An Efficient Algorithm for Level Set Method Preserving Distance Function

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso, Virginia Estellers Casas

The level set method is a popular technique for tracking moving interfaces in several disciplines including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issue ...

Institute of Electrical and Electronics Engineers2012

A Master-Slave Approach for Object Detection and Matching with Fixed and Mobile Cameras

Michel Bierlaire, Murat Kunt, Alexandre Massoud Alahi

Typical object detection algorithms on mobile cameras suffer from the lack of a-priori knowledge on the object to be detected. The variability in the shape, pose, color distribution, and behavior affect the robustness of the detection process. In general, ...

2008

General state-space models : randomised quasi-Monte Carlo methods for general Kalman recursion

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004