Stratified Multi-View Aggregation for Score Distillation
MV-SDI reduces gradient variance in score distillation by aggregating gradients from K views per step. This aggregation uses antithetic antipodal pairs to ensure balanced coverage and removes same-hemisphere clustering. The method improves asset quality and optimization speed by achieving significant gains without retraining or adding memory, showing the benefits stem from the sampling strategy.