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TeethGNN is developed, a novel graph-based framework designed to combine CBCT image features with morphological information for accurate and efficient malocclusion grading, providing an accurate and reliable solution for vision-based clinical measurement and diagnosis.
GuideWalk enables humanoid robots to navigate complex terrains with unprecedented stability by decoupling obstacle avoidance from terrain dynamics.
Humanoid robots can now groove in sync for a full four minutes on stage, thanks to a model-based control framework that anticipates disturbances and proactively adjusts foot placement.
MedVAR leapfrogs existing methods by achieving state-of-the-art medical image generation with an autoregressive architecture designed for both speed and scalability.
