Tayyab Nasir

Reversing the guidance hierarchy in depth super-resolution leads to clearer boundaries and fewer artifacts, outperforming traditional methods in challenging scenarios.

Injecting semantic knowledge from vision transformer embeddings into guided depth super-resolution models dramatically reduces artifacts and sharpens depth boundaries.