Datasets:
FIORD Kitchen_In
| Item | File | Size |
|---|---|---|
| GOFish (Ours) Gaussians | gaussians/point_cloud.ply |
487,945 Gaussians, 121 MB |
| + Geometry Objective Gaussians | gaussians_geo/point_cloud.ply |
486,783 Gaussians, 121 MB |
| + Geometry Objective mesh | mesh/mesh.ply, mesh/mesh.glb |
291 MB PLY |
| Cameras | cameras.json |
408 train and 59 test frames |
Both Gaussian files carry the 3-D Mip filter baked into their scales. Reloading each PLY reproduces the checkpoint's stored positions, rotations, opacities and spherical harmonics exactly, and its filtered scales to float32 precision. EXPORT.json holds the checks and the source checkpoint sha256.
The mesh is byte-identical to the evaluated mesh, sha256 7bba0d0f538c36b03a9c670b42e99047e902394b36c53599b35a5ae009313000.
lidar_alignment.json maps the mesh, Gaussians and cameras into the FIORD LiDAR ground-truth frame used for the paper's geometry scores.
See the top-level README for formats and viewers.