49 citations · 230 across the 30 of their papers we have counts for
4 papers · 2 filters
In-Place Activated BatchNorm for Memory-Optimized Training of DNNs
Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder
In this work we present In-Place Activated Batch Normalization (InPlace-ABN) - a novel approach to drastically reduce the training memory footprint of modern deep neural networks i…
Loss Max-Pooling for Semantic Image Segmentation
Samuel Rota Bulò, Gerhard Neuhold, Peter Kontschieder
We introduce a novel loss max-pooling concept for handling imbalanced training data distributions, applicable as alternative loss layer in the context of deep neural networks for s…
AutoDIAL: Automatic DomaIn Alignment Layers
Fabio Maria Carlucci, Lorenzo Porzi, Barbara Caputo +2
Classifiers trained on given databases perform poorly when tested on data acquired in different settings. This is explained in domain adaptation through a shift among distributions…
Just DIAL: DomaIn Alignment Layers for Unsupervised Domain Adaptation
Fabio Maria Carlucci, Lorenzo Porzi, Barbara Caputo +2
The empirical fact that classifiers, trained on given data collections, perform poorly when tested on data acquired in different settings is theoretically explained in domain adapt…