Self-attention with input-dependent aggregation and soft graph-distance priors outperforms fixed graph convolutions for 2D-to-3D hand pose estimation on FPHA.
Graph at- tention networks
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Rethinking Graph Convolution for 2D-to-3D Hand Pose Lifting
Self-attention with input-dependent aggregation and soft graph-distance priors outperforms fixed graph convolutions for 2D-to-3D hand pose estimation on FPHA.