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This work introduces a novel surface-based diffusion bridge framework DB-SUiT for MRI-to-PET translation that operates natively on the cortical manifold and demonstrates high-fidelity synthesis that substantially outperforms other baselines.
Achieving over 96% success in real-world door traversal tasks, this framework redefines how robots can learn from a single video input.
MultiMoQ achieves smoother viewport playback by increasing goodput and reducing latency, even under challenging network conditions.
JoyAI-Video-Edit achieves real-time video editing at 30 FPS while maintaining high fidelity and temporal consistency, outperforming traditional streaming editors.
Synthesized PET scans from MRI can nearly match the diagnostic accuracy of real PET for Alzheimer's, potentially unlocking wider access to crucial functional insights.
