04b Atto di convegno in volume

A Transfer Learning Approach for Multi-Cue Semantic Place Recognition
Transfer Learning for Visual Place Classification
A Transfer Learning Approach for Multi-Cue Semantic Place Recognition
Visual-inertial Tracking on Android for Augmented Reality Applications
A Discriminative Approach for Appearance Based Loop Closing
Visual-inertial Tracking on Android for Augmented Reality Applications
A Discriminative Approach for Appearance Based Loop Closing
From source to target and back: Symmetric Bi-Directional Adaptive GAN

The effectiveness of GANs in producing images according to a specific visual domain has shown potential in unsupervised domain adaptation. Source labeled images have been modified to mimic target samples for training classifiers in the target domain, and inverse mappings from the target to the...
A deep representation for depth images from synthetic data

Convolutional Neural Networks (CNNs) trained on large scale RGB databases have become the secret sauce in the majority of recent approaches for object categorization from RGB-D data. Thanks to colorization techniques, these methods exploit the filters learned from 2D images to extract meaningful...
Learning the roots of visual domain shift

In this paper we focus on the spatial nature of visual domain shift, attempting to learn where domain adaptation originates in each given image of the source and target set. We borrow concepts and techniques from the CNN visualization literature, and learn domainness maps able to localize the...