The field of multi-object tracking has recently seen a renewed interest ...
Humans can learn incrementally, whereas neural networks forget previousl...
Denoising Diffusion Probabilistic Models have shown an impressive genera...
Rehearsal approaches enjoy immense popularity with Continual Learning (C...
The occurrence of West Nile Virus (WNV) represents one of the most commo...
This work tackles Weakly Supervised Anomaly detection, in which a predic...
This work investigates the entanglement between Continual Learning (CL) ...
Accurate prediction of future human positions is an essential task for m...
The staple of human intelligence is the capability of acquiring knowledg...
Continual Learning (CL) investigates how to train Deep Networks on a str...
In Continual Learning, a Neural Network is trained on a stream of data w...
To achieve robustness in Re-Identification, standard methods leverage
tr...
The recent growth in the number of satellite images fosters the developm...
Neural networks struggle to learn continuously, as they forget the old
k...
Nowadays, Vector-Borne Diseases (VBDs) raise a severe threat for public
...
People re-identification task has seen enormous improvements in the late...
We present a novel and hierarchical approach for supervised classificati...
We propose an unsupervised model for novelty detection. The subject is
t...