Distillation of a 688M-parameter MASt3R teacher yields up to 7x smaller students that retain most lunar reconstruction accuracy and outperform sparse-supervised baselines.
Proceedings of the Royal Society of London
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Geometric Foundation Model Distillation for Efficient Lunar 3D Reconstruction
Distillation of a 688M-parameter MASt3R teacher yields up to 7x smaller students that retain most lunar reconstruction accuracy and outperform sparse-supervised baselines.