Chi-Yuan Ma

Observation-Aligned Mask Priors for Learning Physical Fields from Authentic Occlusions

Observation-Aligned Mask Priors, a framework that learns the distribution of authentic observation masks and uses it to construct context-query partitions for training from incomplete data, is proposed and demonstrated to be an effective alternative to heuristic masking for learning from incomplete physical observation...