Ponències/Comunicacions de congressos: Enviaments recents
Ara es mostren els items 13-24 de 251
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Implications of robot backchannelling in cognitive therapy
(Springer, 2022)
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Accés obertThe social ability of humans to provide active feedback during conversations is known as backchannelling. Recent work has recognised the importance of endowing robots with such social behaviour to make interactions more ... -
A virtual reality framework for fast dataset creation applied to cloth manipulation with automatic semantic labelling
(Institute of Electrical and Electronics Engineers (IEEE), 2023)
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Accés obertTeaching complex manipulation skills, such as folding garments, to a bi-manual robot is a very challenging task, which is often tackled through learning from demonstration. The few datasets of garment-folding demonstrations ... -
Morphological symmetries in robot learning
(OpenReview.net, 2023)
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Accés obertThis work studies the impact of morphological symmetries in learning applications in robotics. Morphological symmetries are a predominant feature in both biological and robotic systems, arising from the presence of planes/axis ... -
Ordinal inverse reinforcement learning applied to robot learning with small data
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
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Accés restringit per política de l'editorialOver the last decade, the ability to teach actions to robots in a user-friendly way has gained relevance, and a practical way of teaching robots a new task is to use Inverse Reinforcement Learning (IRL). In IRL, an expert ... -
Generating attribution maps with disentangled masked backpropagation
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
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Accés obertAttribution map visualization has arisen as one of the most effective techniques to understand the underlying inference process of Convolutional Neural Networks. In this task, the goal is to compute an score for each image ... -
Graph constrained data representation learning for human motion segmentation
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
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Accés obertRecently, transfer subspace learning based approaches have shown to be a valid alternative to unsupervised subspace clustering and temporal data clustering for human motion segmentation (HMS). These approaches leverage ... -
Mixtures of controlled Gaussian processes for dynamical modeling of deformable objects
(Proceedings of Machine Learning Research (PMLR), 2022)
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Accés obertControl and manipulation of objects is a highly relevant topic in Robotics research. Although significant advances have been made over the manipulation of rigid bodies, the manipulation of non-rigid objects is still ... -
Garment manipulation dataset for robot learning by demonstration through a virtual reality framework
(IOS Press, 2022)
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Accés obertBeing able to teach complex capabilities, such as folding garments, to a bi-manual robot is a very challenging task, which is often tackled using learning from demonstration datasets. The few garment folding datasets ... -
Single-view 3d body and cloth reconstruction under complex poses
(Scitepress, 2022)
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Accés obertRecent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn the occupancy status of arbitrarily dense ... -
Recognizing object surface material from impact sounds for robot manipulation
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
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Accés obertWe investigated the use of impact sounds generated during exploratory behaviors in a robotic manipulation setup as cues for predicting object surface material and for recognizing individual objects. We collected and make ... -
Mutual information weighing for probabilistic movement primitives
(2022)
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Accés obertReinforcement Learning (RL) of trajectory data has been used in several fields, and it is of relevance in robot motion learning, in which sampled trajectories are run and their outcome is evaluated with a reward value. The ... -
Learned vertex descent: a new direction for 3D human model fitting
(Springer, 2022)
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Accés obertWe propose a novel optimization-based paradigm for 3D human model fitting on images and scans. In contrast to existing approaches that directly regress the parameters of a low-dimensional statistical body model (e.g. SMPL) ...