19 citations · 21 across the 5 of their papers we have counts for
10 papers
A patch-based architecture for multi-label classification from single label annotations
Warren Jouanneau, Aurélie Bugeau, Marc Palyart +2
In this paper, we propose a patch-based architecture for multi-label classification problems where only a single positive label is observed in images of the dataset. Our contributi…
Analysis of Different Losses for Deep Learning Image Colorization
Coloma Ballester, Aurélie Bugeau, Hernan Carrillo +4
Image colorization aims to add color information to a grayscale image in a realistic way. Recent methods mostly rely on deep learning strategies. While learning to automatically co…
An Analysis of Generative Methods for Multiple Image Inpainting
Coloma Ballester, Aurelie Bugeau, Samuel Hurault +2
Image inpainting refers to the restoration of an image with missing regions in a way that is not detectable by the observer. The inpainting regions can be of any size and shape. Th…
Influence of Color Spaces for Deep Learning Image Colorization
Coloma Ballester, Aurélie Bugeau, Hernan Carrillo +4
Colorization is a process that converts a grayscale image into a color one that looks as natural as possible. Over the years this task has received a lot of attention. Existing col…
3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings
Giorgia Pitteri, Aurélie Bugeau, Slobodan Ilic +1
We present an approach for detecting and estimating the 3D poses of objects in images that requires only an untextured CAD model and no training phase for new objects. Our approach…
Multi-task deep learning for image segmentation using recursive approximation tasks
Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis +3
Fully supervised deep neural networks for segmentation usually require a massive amount of pixel-level labels which are manually expensive to create. In this work, we develop a mul…