Umberto Michieli

Online Continual Learning for Robust Indoor Object Recognition

2023

Vision systems mounted on home robots need to interact with unseen classes in changing environments. Robots have limited computational resources, labelled data and storage capability. These requirements pose some unique challenges: models should adapt without …

Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics

2024 · arXiv (Cornell University)

Developing a reliable vision system is a fundamental challenge for robotic technologies (e.g., indoor service robots and outdoor autonomous robots) which can ensure reliable navigation even in challenging environments such as adverse weather conditions (e.g., …