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J-ORA: A Framework and Multimodal Dataset for Japanese Object Identification, Reference, Action Prediction in Robot Perception

arXiv — cs.CV•Tuesday, October 28, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
The introduction of J-ORA marks a significant advancement in robot perception, providing a comprehensive multimodal dataset tailored for Japanese human-robot interactions. This framework not only enhances object identification and reference resolution but also aids in predicting actions, making robots more intuitive and effective in understanding their environment. As robotics continues to evolve, J-ORA's detailed annotations will play a crucial role in improving communication between humans and machines, ultimately leading to more sophisticated and responsive robotic systems.
— Curated by the World Pulse Now AI Editorial System
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