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Found 7 papers, 0 papers with code
The Imaginative Generative Adversarial Network: Automatic Data Augmentation for Dynamic Skeleton-Based Hand Gesture and Human Action Recognition
Insufficient training data results in over-fitting and data augmentation is one approach to address this challenge.
Reinforcement Learning in Presence of Discrete Markovian Context Evolution
We consider a context-dependent Reinforcement Learning (RL) setting, which is characterized by: a) an unknown finite number of not directly observable contexts; b) abrupt (discontinuous) context changes occurring during an episode; and c) Markovian context evolution.
XAIR: A Framework of Explainable AI in Augmented Reality
The framework was based on a multi-disciplinary literature review of XAI and HCI research, a large-scale survey probing 500+ end-users' preferences for AR-based explanations, and three workshops with 12 experts collecting their insights about XAI design in AR.
Encode-Store-Retrieve: Enhancing Memory Augmentation through Language-Encoded Egocentric Perception
Additionally, in a user study, our system received a higher mean response score of 4. 13/5 compared to the human participants' score of 2. 46/5 on real-life episodic memory tasks.
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques
However, the task of prompting large language models to specialize in specific text prediction tasks can be challenging, particularly for designers without expertise in prompt engineering.
Simultaneous Gesture Classification and Localization with an Automatic Gesture Annotation Model
Training a real-time gesture recognition model heavily relies on annotated data.
Towards Open-World Gesture Recognition
We propose leveraging continual learning to make machine learning models adaptive to new tasks without degrading performance on previously learned tasks.
