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By reformulating spatial-temporal reasoning into localized coupled graph aggregation, HSTGFormer significantly enhances 3D human pose estimation accuracy while maintaining computational efficiency.
Turns out, you can predict what drivers will do next with surprising accuracy (90%) using EEG data, even in messy, real-world driving conditions.
