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Online Learning of Reusable Abstract Models for Object Goal Navigation
- Tommaso Campari, Leonardo Lamanna, P. Traverso, L. Serafini, Lamberto Ballan
- Computer ScienceComputer Vision and Pattern Recognition
- 4 March 2022
In this paper, we present a novel approach to incrementally learn an Abstract Model of an unknown environment, and show how an agent can reuse the learned model for tackling the Object Goal…
Retrospectives on the Embodied AI Workshop
This analysis focuses on 13 challenges presented at the Embodied AI Workshop at CVPR, grouped into three themes: visual navigation, rearrangement, and embodied vision-and-language.
Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions
Deep Symbolic Learning is proposed, a NeSy system that learns NeSy-functions, i.e. the composition of a (set of) perception functions which map continuous data to discrete symbols, and a symbolic function over the set of symbols.