Publication

Hierarchical Indexing using R-trees for Replica Detection

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Los Alamitos2023

CLIP the Gap: A Single Domain Generalization Approach for Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well studied for image classification, the literature on SDG object detection remai ...

Los Alamitos2023

Publish your thesis while respecting copyright rules

Marjorie Platon, Manon Velasco

It is very common to reuse published (or unpublished) content in a thesis (e.g. in the case of the theses made of a compilation of published articles). It is therefore important to ensure that the use (or reuse) is possible and to ask for authorizations fr ...

2021

Index-Driven Digitization and Indexation of Historical Archives

Maud Ehrmann, Giovanni Colavizza

The promise of digitization of historical archives lies in their indexation at the level of contents. Unfortunately, this kind of indexation does not scale, if done manually. In this article we present a method to bootstrap the deployment of a content-base ...

2019

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

Localizing Polygonal Objects in Man-Made Environments

Xiaolu Sun

Object detection is a significant challenge in Computer Vision and has received a lot of attention in the field. One such challenge addressed in this thesis is the detection of polygonal objects, which are prevalent in man-made environments. Shape analysis ...

EPFL2015

Annihilation-driven Localised Image Edge Models

Martin Vetterli, Thierry Blu, Hanjie Pan

We propose a novel edge detection algorithm with sub-pixel accuracy based on annihilation of signals with finite rate of innovation. We show that the Fourier domain annihilation equations can be interpreted as spatial domain multiplications. From this new ...

IEEE2015

Keypoint Recognition using Random Forests and Random Ferns

Pascal Fua, Vincent Lepetit

In many 3-D object-detection and pose-estimation problems, run-time performance is of critical importance. However, there usually is time to train the system. We introduce an approach that takes advantage of this fact by formulating wide-baseline matching ...

Springer2013