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It is suggested that audio is an underexplored but highly informative modality for sports highlight detection and should be treated as a primary signal rather than merely an auxiliary cue.
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.
CODE outperforms prior methods in Open World Object Detection by effectively balancing known and unknown object detection through innovative calibration and suppression techniques.
Vision-based social navigation is still far from solved, with critical safety deficits overshadowing social etiquette in robotic interactions.
HyWorldVLA achieves unprecedented noise robustness in autonomous driving by seamlessly integrating pixel-level grounding with latent representation learning.
SeamGen learns from professional seam layouts to generate UV seams that artists actually prefer, outperforming traditional methods in both quality and alignment.
Temporal Feature Distillation boosts PES accuracy by over 4 points with less than 10% labeled data, outperforming traditional methods that struggle with subtle motion cues.