Incomplete multi-modal clustering (IMmC) is challenging due to the unexpected missing of
some modalities in data. A key to this problem is to explore complementarity information …

Nowadays, the abuse of deepfakes is a well-known issue since deepfakes can lead to
severe security and privacy problems. And this situation is getting worse, as attackers are no …

Audiovisual news is a critical cultural phenomenon that has been influencing audience
worldviews for more than a hundred years. To understand historical trends in multimodal …

Ensembles of independently trained deep neural networks yield uncertainty estimates that
rival Bayesian networks in performance. They also offer sizable improvements in terms of …

Video instance segmentation, also known as multi-object tracking and segmentation, is an
emerging computer vision research area introduced in 2019, aiming at detecting …

Existing Graph Neural Networks (GNNs) are limited to process graphs each of whose
vertices is represented by a vector or a single value, limited their representing capability to …

In this paper, we propose a novel approach to improve instance segmentation and
classification tasks by incorporating SegmentAnything [1] before using graph neural network …

Abstract Graph Neural Networks (GNNs) have become important in the machine learning
landscape because of their ability to model complex, structured data. This thesis presents …

A mobile robot, instructed by a human operator, acts in an environment with many other
objects. However, for an autonomous robot, human instructions should be minimal and only …