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Found 8 papers, 3 papers with code
GazeMotion: Gaze-guided Human Motion Forecasting
We present GazeMotion, a novel method for human motion forecasting that combines information on past human poses with human eye gaze.
GazeMoDiff: Gaze-guided Diffusion Model for Stochastic Human Motion Prediction
Human motion prediction is important for virtual reality (VR) applications, e. g., for realistic avatar animation.
Pose2Gaze: Generating Realistic Human Gaze Behaviour from Full-body Poses using an Eye-body Coordination Model
While generating realistic body movements, e. g., for avatars in virtual reality, is widely studied in computer vision and graphics, the generation of eye movements that exhibit realistic coordination with the body remains under-explored.
Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models
Humans excel at robust bipedal walking in complex natural environments.
Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks
Humans are able to outperform robots in terms of robustness, versatility, and learning of new tasks in a wide variety of movements.
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
Muscle-actuated organisms are capable of learning an unparalleled diversity of dexterous movements despite their vast amount of muscles.
Biomechanical surrogate modelling using stabilized vectorial greedy kernel methods
Greedy kernel approximation algorithms are successful techniques for sparse and accurate data-based modelling and function approximation.
Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping
An important aspect of morphological computation is that it cannot be assigned to an embodied system per se, but that it is, as we show, behavior- and state-dependent.
