Masked depth modeling with sensor-validity masking: reports best RMSE on 7 of 8 masked/sparse depth benchmarks, plus a controlled encoder-init study[R]

The core idea in masked depth modeling is to treat the sensor's own missing regions as the masking signal rather than using random block dropout. Specular highlights, transparent surfaces, and textureless areas where RGB-D cameras return no valid depth become the natural training target. The model t