JUMP-Hand: Learning Joint-wise Uncertainty to Gate Mixture of View Experts for Multi-View 3D Hand Reconstruction
We propose JUMP-Hand, a novel multi-view 3D hand reconstruction method that explicitly models probabilistic joint-wise uncertainty as a gating mechanism for multi-view fusion. Existing approaches usually rely on naive pooling or implicit attention, overlooking that each hand joint exhibits varying v