Learning affordances in object-centric generative models
Given visual observations of a reaching task together with a stick-like tool, we propose a novel approach that learns to exploit task-relevant object affordances by combining generative modelling with a task-based performance predictor. The embedding learned by the generative model captures the fact...
Main Authors: | Wu, Y, Kasewa, S, Groth, O, Salter, S, Sun, L, Parker Jones, O, Posner, H |
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Format: | Conference item |
Language: | English |
Published: |
International Conference on Machine Learning
2020
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