1,405 research outputs found
Learning to Act Properly: Predicting and Explaining Affordances from Images
We address the problem of affordance reasoning in diverse scenes that appear
in the real world. Affordances relate the agent's actions to their effects when
taken on the surrounding objects. In our work, we take the egocentric view of
the scene, and aim to reason about action-object affordances that respect both
the physical world as well as the social norms imposed by the society. We also
aim to teach artificial agents why some actions should not be taken in certain
situations, and what would likely happen if these actions would be taken. We
collect a new dataset that builds upon ADE20k, referred to as ADE-Affordance,
which contains annotations enabling such rich visual reasoning. We propose a
model that exploits Graph Neural Networks to propagate contextual information
from the scene in order to perform detailed affordance reasoning about each
object. Our model is showcased through various ablation studies, pointing to
successes and challenges in this complex task
Bond relaxation, electronic and magnetic behavior of 2D metals structures Y on Li(110) surface
We investigated the bond, electronic and magnetic behavior of adsorption
Yttrium atoms on Lithium (110) surface using a combination of
Bond-order-length-strength(BOLS) correlation and density-functional
theory(DFT). We found that adsorption Y atoms on Li(110) surfaces form
two-dimensional (2D) geometric structures of hexagon, nonagon, solid hexagonal,
quadrangle and triangle. The consistent with the magnetic moment are
6.66{\mu}B, 5.54{\mu}B, 0.28{\mu}B, 1.04{\mu}B, 2.81{\mu}B, respectively. In
addition, this work could pave the way for design new 2D metals electronic and
magnetic properties
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