The aim of this paper is to give an overview of domain adaptation and transfer learning with
a specific view on visual applications. After a general motivation, we first position domain …

Estimating the pose of a human in 3D given an image or a video has recently received
significant attention from the scientific community. The main reasons for this trend are the …

We introduce a new dataset, Human3. 6M, of 3.6 Million accurate 3D Human poses,
acquired by recording the performance of 5 female and 6 male subjects, under 4 different …

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 …

A key assumption of top-down human pose estimation approaches is their expectation of
having a single person/instance present in the input bounding box. This often leads to …

Abstract Current Domain Adaptation (DA) methods based on deep architectures assume
that the source samples arise from a single distribution. However, in practice most datasets …

The increasing use of data-driven decision support systems in industry and governments is
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …

Automatic facial action unit (AFA) detection from video is a long-standing problem in facial
expression analysis. Most approaches emphasize choices of features and classifiers. They …

Automatic facial action unit (AU) and expression detection from videos is a long-standing
problem. The problem is challenging in part because classifiers must generalize to …

Abstract Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain
gap between a labeled source dataset and an unlabelled target dataset for regression …