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This paper investigates using a Transformer-based generative model to learn emotional body motions from motion-capture data of Japanese actors, generating motions conditioned on discrete emotion labels. Evaluations show the generated motions improve emotion recognition when used for data augmentation and enable smooth transitions between emotion intensities.
Brooklyn-based startup Reflex Robotics demonstrated its warehouse robots, which simulate human interaction using non-verbal cues like nodding, shaking head, rolling, and eye tracking. The robots are about to be deployed in restaurants and cafes, where they will handle tasks such as pouring drinks, organizing items, and making burgers.