| # 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 | |
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| 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. |
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