59 citations · 59 across the 3 of their papers we have counts for
3 papers
MVMO: A Multi-Object Dataset for Wide Baseline Multi-View Semantic Segmentation
Aitor Alvarez-Gila, Joost van de Weijer, Yaxing Wang +1
We present MVMO (Multi-View, Multi-Object dataset): a synthetic dataset of 116,000 scenes containing randomly placed objects of 10 distinct classes and captured from 25 camera loca…
Self-supervised blur detection from synthetically blurred scenes
Aitor Alvarez-Gila, Adrian Galdran, Estibaliz Garrote +1
Blur detection aims at segmenting the blurred areas of a given image. Recent deep learning-based methods approach this problem by learning an end-to-end mapping between the blurred…
Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis
Adrian Galdran, Aitor Alvarez-Gila, Maria Ines Meyer +7
Dermoscopic skin images are often obtained with different imaging devices, under varying acquisition conditions. In this work, instead of attempting to perform intensity and color…