https://tatbeclin1chemical.com..../advancements-within
Additionally, combining DSTD-GC with prior comprehension of bodily connection and temporal sequence, we propose a powerful spatiotemporal graph convolutional network, namely DSTD-GCN. DSTD-GCN's performance on the Human36M, Carnegie Mellon University (CMU) Mocap, and 3DPW datasets demonstrates an impressive improvement in prediction accuracy, surpassing state-of-the-art methods by 39% to 87% while drastically reducing the parameter count by 550% to 969%. The s
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