MV-SDI aggregates K-view gradients per step via accumulation and antithetic pairs at fixed UNet budget, raising CLIP R-Precision from 74.8% to 83.8% (K=2) and halving steps while keeping the 2D prior frozen.
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Variance Reduction on the Camera Axis: Multi-View Score Distillation for 3D
MV-SDI aggregates K-view gradients per step via accumulation and antithetic pairs at fixed UNet budget, raising CLIP R-Precision from 74.8% to 83.8% (K=2) and halving steps while keeping the 2D prior frozen.