# Sliding-Window Slice Latents

SILSA is a topology-aware high-resolution 3D generation framework that replaces voxel tokens with a fixed set of overlapping slice latents along the three canonical axes, combining a SliceVAE, a Volumetric Anchor Lattice, and slice-level persistent-homology supervision to raise PSNR from 30.12 to 32.74, coverage from 73.12% to 79.08%, and reduce Betti error by 9.2% on image-to-3D generation while using only 384 tokens, cutting training memory by 40.4% and inference time by 58.5%.

SILSA is a topology-aware high-resolution 3D generation framework that replaces voxel tokens with a fixed set of overlapping slice latents along the three canonical axes, combining a SliceVAE, a Volumetric Anchor Lattice, and slice-level persistent-homology supervision to raise PSNR from 30.12 to 32.74, coverage from 73.12% to 79.08%, and reduce Betti error by 9.2% on image-to-3D generation while using only 384 tokens, cutting training memory by 40.4% and inference time by 58.5%.