# Persistent Spatial Memory

GeoVerse performs diffusion generation inside the geometric latent space of a pretrained 3D foundation model (DA3), injects frozen Wan2.2 VACE video features into the denoiser through a ControlNet-style adapter, and uses a continuously updated colored point-cloud spatial memory to reproject history as target-aligned guidance, synthesizing cross-view consistent novel views from sparse inputs; across DL3DV, RealEstate10K, Mip-NeRF 360, and ScanNetV2 it reports better visual quality and geometric consistency, with PSNR 2.23 dB higher than GLD on DL3DV and ATE 32.4% lower than GLD on Mip-NeRF 360, while reflow distillation brings inference from over 100 seconds to under 10 seconds.

GeoVerse performs diffusion generation inside the geometric latent space of a pretrained 3D foundation model (DA3), injects frozen Wan2.2 VACE video features into the denoiser through a ControlNet-style adapter, and uses a continuously updated colored point-cloud spatial memory to reproject history as target-aligned guidance, synthesizing cross-view consistent novel views from sparse inputs; across DL3DV, RealEstate10K, Mip-NeRF 360, and ScanNetV2 it reports better visual quality and geometric consistency, with PSNR 2.23 dB higher than GLD on DL3DV and ATE 32.4% lower than GLD on Mip-NeRF 360, while reflow distillation brings inference from over 100 seconds to under 10 seconds.