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SAR: generalization of physiological agility and dexterity via synergistic action representation
Autonomous Robots, 2023Learning effective continuous control policies in high-dimensional systems, including musculoskeletal agents, remains a significant challenge. Over the course of biological evolution, organisms have developed robust mechanisms for overcoming this ...
C. Berg, V. Caggiano, Vikash Kumar
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Self-supervised 3D Skeleton Action Representation Learning with Motion Consistency and Continuity
IEEE International Conference on Computer Vision, 2021Recently, self-supervised learning (SSL) has been proved very effective and it can help boost the performance in learning representations from unlabeled data in the image domain.
Yukun Su, Guosheng Lin, Qingyao Wu
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Modeling the Uncertainty for Self-supervised 3D Skeleton Action Representation Learning
ACM Multimedia, 2021Self-supervised learning (SSL) has been proved very effective in learning representations from unlabeled data in language and vision domains. Yet, very few instrumental self-supervised approaches exist for 3D skeleton action understanding, and directly ...
Yukun Su +4 more
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Electrophysiology of Action Representation
Journal of Clinical Neurophysiology, 2004We continuously act on objects, on other individuals, and on ourselves, and actions represent the only way we have to manifest our own desires and goals. In the last two decades, electrophysiological experiments have demonstrated that actions are stored in the brain according to a goal-related organization.
FADIGA, Luciano, CRAIGHERO, Laila
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InfoGCN: Representation Learning for Human Skeleton-based Action Recognition
Computer Vision and Pattern Recognition, 2022Human skeleton-based action recognition offers a valuable means to understand the intricacies of human behavior because it can handle the complex relationships between physical constraints and intention.
Hyung-gun Chi +5 more
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Concrete Action Representation Model: From Neuroscience to Robotics
IEEE Transactions on Cognitive and Developmental Systems, 2020How can robotics benefit from neuroscience to build a unified framework that computes actions for both locomotion and manipulation tasks? Inspired by the hierarchical neural control of movement from cortex to spinal cord, we propose a model that ...
John Nassour +3 more
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Action representation deficits in adolescents with developmental dyslexia.
Journal of Neuropsychology, 2020Developmental dyslexia (DD), a severe and frequent disorder of reading acquisition, is characterized by a diversity of cognitive and motor deficits whose interactions still remain under debate.
Alice van de Walle de Ghelcke +4 more
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Goal Representations in Imitative Actions
2002Item does not contain ...
Bekkering, H., Prinz, W.
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2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021
Micro-expressions recognition is a challenge because it involves subtle variations in facial organs. In this paper, first, we propose a novel pipeline to learn a facial graph (nodes and edges) representation to capture these local subtle variations.
Ling Lei +3 more
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Micro-expressions recognition is a challenge because it involves subtle variations in facial organs. In this paper, first, we propose a novel pipeline to learn a facial graph (nodes and edges) representation to capture these local subtle variations.
Ling Lei +3 more
semanticscholar +1 more source
Neural Representations for Action
Reviews in the Neurosciences, 1996Goal directed behaviour is often internally generated which implies that the generation of action involves a representational step. One of the challenges of cognitive neuroscience is to discover the neural mechanism that underlies the representation of both intention and goal and fuses them into an integrated action.
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