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Found 3 papers, 1 papers with code
Multi-label affordance mapping from egocentric vision
We use this method to build the largest and most complete dataset on affordances based on the EPIC-Kitchen dataset, EPIC-Aff, which provides interaction-grounded, multi-label, metric and spatial affordance annotations.
Bayesian Deep Learning for Affordance Segmentation in images
We present a novel Bayesian deep network to detect affordances in images, at the same time that we quantify the distribution of the aleatoric and epistemic variance at the spatial level.
Bayesian deep learning of affordances from RGB images
Our Bayesian model is able to capture both the aleatoric uncertainty from the scene and the epistemic uncertainty associated with the model and previous learning process.
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