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Nanjing University of Science and Technology
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Emotion-controllable portrait animation can now be achieved in real-time with a single training instance, revolutionizing the efficiency and expressiveness of animated avatars.
Emotional avatars can now be synthesized in real-time with unprecedented expressiveness and control, thanks to a novel approach that combines audio features and Gaussian attributes.
PhysFlow achieves unprecedented robustness in rPPG estimation by decoupling signal components, outperforming existing methods even in the most challenging conditions.
By cleverly fusing spectral and spatial information, ASGNet achieves state-of-the-art polyp segmentation, suggesting that moving beyond purely spatial processing can unlock significant gains in medical image analysis.
