Upload GOFish scenes

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.avro filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+FIORD_Bridge_Out/gaussians/appearance.json filter=lfs diff=lfs merge=lfs -text
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+FIORD_Bridge_Out/mesh/mesh.ply filter=lfs diff=lfs merge=lfs -text
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+FIORD_Hall_In/gaussians/appearance.json filter=lfs diff=lfs merge=lfs -text
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+FIORD_Hall_In/mesh/mesh.ply filter=lfs diff=lfs merge=lfs -text
+FIORD_Kitchen_In/gaussians/appearance.json filter=lfs diff=lfs merge=lfs -text
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+FullCircle_dark/gaussians/appearance.json filter=lfs diff=lfs merge=lfs -text
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+FullCircle_dark/mesh/mesh.glb filter=lfs diff=lfs merge=lfs -text
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FIORD_Bridge_Out/MANIFEST.json

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+{
+ "scene": "FIORD_Bridge_Out",
+ "files": [
+  {
+   "path": "PACKAGE_EXPORT.json",
+   "bytes": 2272,
+   "sha256": "f88f42bccfeb7c3e70eebd27ff4fa07d738d1c460140f82d381fe4f900f1ccef"
+  },
+  {
+   "path": "README.md",
+   "bytes": 993,
+   "sha256": "09ba7532ccd530368daaab451d7b0491e47b0992c3b955a477d7cce7f34e3ade"
+  },
+  {
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+   "sha256": "2d12b9eb03cef159fdc42dad9eb79c0c759db365ee1ad82ba0ec593f3b403f28"
+  },
+  {
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+   "sha256": "814cc02734c659bfd560cc576cda42a36c33e63a16107cab05c742c9520786cb"
+  },
+  {
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+  },
+  {
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+   "sha256": "30131812f4c8666077665f301764e55fbc828e5f0758d2acc3133f91d9219151"
+  },
+  {
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+   "sha256": "d61d979df019a3a155cb617de02b92f333885a58c3cfb9a35762462c4e607286"
+  },
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+   "sha256": "afd1cf004d2f104c89141b64ab7505abc80eff5883766512f99b26cd095adf1f"
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+  {
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+   "sha256": "12b9fbf5b015f2f29cd0573d2405b3156f07905d1cc975c525e49cef544eed2c"
+  },
+  {
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+   "bytes": 954,
+   "sha256": "98b42d454f055f5a3cddeb62bbc3c429236944f3626b812081ecbc2604c1266c"
+  },
+  {
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+   "sha256": "6d77fda5a159ebf938d1f7c085c059667436b2fa59b237fc775e208e1a57dd8a"
+  },
+  {
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+   "sha256": "9fc7319415400b646aa17899a4548526bf10cc7a445e7cdfbd26d823d4968d01"
+  }
+ ]
+}

FIORD_Bridge_Out/PACKAGE_EXPORT.json

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+{
+ "dataset": "FIORD",
+ "scene": "Bridge_Out",
+ "gaussians": {
+  "source_checkpoint": "/opt/dlami/nvme/gpv/fest_k50_radial_ff_apo/train/checkpoints/c35.pt",
+  "source_sha256": "f0ddc5ac42b1257c4d34149bb2b158695a0e3ff254a91ce2e4ae3c8e79a078a7",
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+  "sh_degree": 3,
+  "feature_type": "sh",
+  "filter_note": [
+   "3-D Mip filter baked: scale = sqrt(exp(scale)^2 + filter_3D^2), isotropic; opacity unchanged (physical Mip3D, no volume-ratio opacity compensation, as in the paper)"
+  ],
+  "mip3d_filter_schema": "gofish.physical_mip3d_filter.checkpoint.v2",
+  "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
+  "verify": {
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+   "scale_eff_max_rel": 8.13790919096391e-08,
+   "opacity_max_abs": 0.0,
+   "rotation_max_abs": 0.0,
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+  "ply_bytes": 174271627
+ },
+ "gaussians_geo": {
+  "source_checkpoint": "/opt/dlami/nvme/gpv/fest_k50_radial_ff/train/checkpoints/c35.pt",
+  "source_sha256": "038f122e6ec8177c82faeb5b95358965c3034c2a8cd14420ed95506a08e0a30f",
+  "global_step": 35000,
+  "num_gaussians": 700240,
+  "sh_degree": 3,
+  "feature_type": "sh",
+  "filter_note": [
+   "3-D Mip filter baked: scale = sqrt(exp(scale)^2 + filter_3D^2), isotropic; opacity unchanged (physical Mip3D, no volume-ratio opacity compensation, as in the paper)"
+  ],
+  "mip3d_filter_schema": "gofish.physical_mip3d_filter.checkpoint.v2",
+  "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
+  "verify": {
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+   "scale_eff_max_rel": 4.5953239435903015e-08,
+   "opacity_max_abs": 0.0,
+   "rotation_max_abs": 0.0,
+   "sh_dc_max_abs": 0.0,
+   "sh_rest_max_abs": 0.0
+  },
+  "ply_sha256": "12b9fbf5b015f2f29cd0573d2405b3156f07905d1cc975c525e49cef544eed2c",
+  "ply_bytes": 173661051
+ },
+ "mesh": {
+  "source": "/opt/dlami/nvme/gpv/e12/vig_fest_k50_radial_ff/mesh.ply",
+  "source_sha256": "9fc7319415400b646aa17899a4548526bf10cc7a445e7cdfbd26d823d4968d01",
+  "sha256": "9fc7319415400b646aa17899a4548526bf10cc7a445e7cdfbd26d823d4968d01",
+  "bytes": 420156088
+ },
+ "n_frames": {
+  "train": 840,
+  "test": 120
+ }
+}

FIORD_Bridge_Out/README.md

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+# FIORD Bridge_Out
+
+| Item | File | Size |
+|---|---|---|
+| GOFish (Ours) Gaussians | `gaussians/point_cloud.ply` | 702,702 Gaussians, 174 MB |
+| + Geometry Objective Gaussians | `gaussians_geo/point_cloud.ply` | 700,240 Gaussians, 174 MB |
+| + Geometry Objective mesh | `mesh/mesh.ply`, `mesh/mesh.glb` | 420 MB PLY |
+| Cameras | `cameras.json` | 840 train and 120 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 `9fc7319415400b646aa17899a4548526bf10cc7a445e7cdfbd26d823d4968d01`.
+`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.

FIORD_Bridge_Out/gaussians/EXPORT.json

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+{
+ "source_checkpoint": "/opt/dlami/nvme/gpv/fest_k50_radial_ff_apo/train/checkpoints/c35.pt",
+ "source_sha256": "f0ddc5ac42b1257c4d34149bb2b158695a0e3ff254a91ce2e4ae3c8e79a078a7",
+ "global_step": 35000,
+ "num_gaussians": 702702,
+ "sh_degree": 3,
+ "feature_type": "sh",
+ "filter_note": [
+  "3-D Mip filter baked: scale = sqrt(exp(scale)^2 + filter_3D^2), isotropic; opacity unchanged (physical Mip3D, no volume-ratio opacity compensation, as in the paper)"
+ ],
+ "mip3d_filter_schema": "gofish.physical_mip3d_filter.checkpoint.v2",
+ "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
+ "verify": {
+  "positions_max_abs": 0.0,
+  "scale_eff_max_rel": 8.13790919096391e-08,
+  "opacity_max_abs": 0.0,
+  "rotation_max_abs": 0.0,
+  "sh_dc_max_abs": 0.0,
+  "sh_rest_max_abs": 0.0
+ },
+ "ply_sha256": "30131812f4c8666077665f301764e55fbc828e5f0758d2acc3133f91d9219151",
+ "ply_bytes": 174271627
+}

FIORD_Bridge_Out/gaussians/appearance.json

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+oid sha256:dd56a3876b90712d6dbb459bd4cde384b4b27fb04750434fafe977b24bf723e6
+size 11013350

FIORD_Bridge_Out/gaussians/point_cloud.ply

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+version https://git-lfs.github.com/spec/v1
+oid sha256:30131812f4c8666077665f301764e55fbc828e5f0758d2acc3133f91d9219151
+size 174271627

FIORD_Bridge_Out/gaussians_geo/EXPORT.json

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+{
+ "source_checkpoint": "/opt/dlami/nvme/gpv/fest_k50_radial_ff/train/checkpoints/c35.pt",
+ "source_sha256": "038f122e6ec8177c82faeb5b95358965c3034c2a8cd14420ed95506a08e0a30f",
+ "global_step": 35000,
+ "num_gaussians": 700240,
+ "sh_degree": 3,
+ "feature_type": "sh",
+ "filter_note": [
+  "3-D Mip filter baked: scale = sqrt(exp(scale)^2 + filter_3D^2), isotropic; opacity unchanged (physical Mip3D, no volume-ratio opacity compensation, as in the paper)"
+ ],
+ "mip3d_filter_schema": "gofish.physical_mip3d_filter.checkpoint.v2",
+ "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
+ "verify": {
+  "positions_max_abs": 0.0,
+  "scale_eff_max_rel": 4.5953239435903015e-08,
+  "opacity_max_abs": 0.0,
+  "rotation_max_abs": 0.0,
+  "sh_dc_max_abs": 0.0,
+  "sh_rest_max_abs": 0.0
+ },
+ "ply_sha256": "12b9fbf5b015f2f29cd0573d2405b3156f07905d1cc975c525e49cef544eed2c",
+ "ply_bytes": 173661051
+}

FIORD_Bridge_Out/gaussians_geo/appearance.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:afd1cf004d2f104c89141b64ab7505abc80eff5883766512f99b26cd095adf1f
+size 11015892

FIORD_Bridge_Out/gaussians_geo/point_cloud.ply

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FIORD_Bridge_Out/lidar_alignment.json

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+ "use": "x_gt = (transform_mesh_to_gt @ [x, 1])[:3]; the paper scores F-score at 10 cm in this frame.",
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FIORD_Building_In/PACKAGE_EXPORT.json

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+{
+ "dataset": "FIORD",
+ "scene": "Building_In",
+ "gaussians": {
+  "source_checkpoint": "/opt/dlami/nvme/gpv/para_k50_radial_ff_apo/train/checkpoints/c35.pt",
+  "source_sha256": "6c1329bb9e81be1125b0e36a01974c262c04839aba9f6d6ce54789dc8aba5fcd",
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+  "test": 58
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+}

FIORD_Building_In/README.md

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+# FIORD Building_In
+
+| Item | File | Size |
+|---|---|---|
+| GOFish (Ours) Gaussians | `gaussians/point_cloud.ply` | 489,734 Gaussians, 121 MB |
+| + Geometry Objective Gaussians | `gaussians_geo/point_cloud.ply` | 492,218 Gaussians, 122 MB |
+| + Geometry Objective mesh | `mesh/mesh.ply`, `mesh/mesh.glb` | 282 MB PLY |
+| Cameras | `cameras.json` | 402 train and 58 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 `c603b53a1a1d2b1468b1a07d272ca5931ec0e00d87eefe0b244a5d13264ba053`.
+`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.

FIORD_Building_In/gaussians/EXPORT.json

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+ "source_checkpoint": "/opt/dlami/nvme/gpv/para_k50_radial_ff_apo/train/checkpoints/c35.pt",
+ "source_sha256": "6c1329bb9e81be1125b0e36a01974c262c04839aba9f6d6ce54789dc8aba5fcd",
+ "global_step": 35000,
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+ "filter_note": [
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+ ],
+ "mip3d_filter_schema": "gofish.physical_mip3d_filter.checkpoint.v2",
+ "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
+ "verify": {
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+ "ply_sha256": "024f1be41d59fa0ad48b5a653e155470476f32e40594527bd931fa578ba1d811",
+ "ply_bytes": 121455563
+}

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FIORD_Building_In/gaussians_geo/EXPORT.json

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+ "source_sha256": "119b8188d624c94817c13a3192bf21e0c2079592c867756e74979391146741c9",
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+ ],
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+ "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
+ "verify": {
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FIORD_Building_In/lidar_alignment.json

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+ "use": "x_gt = (transform_mesh_to_gt @ [x, 1])[:3]; the paper scores F-score at 10 cm in this frame.",
+ "source_sha256": "3cd48adf002b2528bbc053a68357b5581ca78e22ff3fa586cd627ac09da6fbac"
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FIORD_Building_In/mesh/mesh.glb

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FIORD_Corridor_Out/MANIFEST.json

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FIORD_Corridor_Out/PACKAGE_EXPORT.json

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+{
+ "dataset": "FIORD",
+ "scene": "Corridor_Out",
+ "gaussians": {
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+}

FIORD_Corridor_Out/README.md

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+# FIORD Corridor_Out
+
+| Item | File | Size |
+|---|---|---|
+| GOFish (Ours) Gaussians | `gaussians/point_cloud.ply` | 530,351 Gaussians, 132 MB |
+| + Geometry Objective Gaussians | `gaussians_geo/point_cloud.ply` | 540,763 Gaussians, 134 MB |
+| + Geometry Objective mesh | `mesh/mesh.ply`, `mesh/mesh.glb` | 303 MB PLY |
+| Cameras | `cameras.json` | 426 train and 61 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 `60b04d499df86cfc8933175dcbc6d3a8152434d734fa0857ecc3382786e5d0ce`.
+See the top-level README for formats and viewers.

FIORD_Corridor_Out/gaussians/EXPORT.json

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+{
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+ "source_sha256": "c28a3d6602c2ca6349171d2e8681ee01eff3f319c0709d893df85370e53809c3",
+ "global_step": 35000,
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FIORD_Corridor_Out/gaussians_geo/EXPORT.json

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FIORD_Hall_In/MANIFEST.json

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FIORD_Hall_In/PACKAGE_EXPORT.json

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+{
+ "dataset": "FIORD",
+ "scene": "Hall_In",
+ "gaussians": {
+  "source_checkpoint": "/opt/dlami/nvme/gpv/sport_k50_radial_ff_apo/train/checkpoints/c35.pt",
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+  "test": 141
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+}

FIORD_Hall_In/README.md

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+# FIORD Hall_In
+
+| Item | File | Size |
+|---|---|---|
+| GOFish (Ours) Gaussians | `gaussians/point_cloud.ply` | 1,014,691 Gaussians, 252 MB |
+| + Geometry Objective Gaussians | `gaussians_geo/point_cloud.ply` | 1,012,149 Gaussians, 251 MB |
+| + Geometry Objective mesh | `mesh/mesh.ply`, `mesh/mesh.glb` | 613 MB PLY |
+| Cameras | `cameras.json` | 980 train and 141 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 `57529e37e71d0de10cedd060198874b50a79e226c66da8169b4fe36e3a938a94`.
+`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.

FIORD_Hall_In/gaussians/EXPORT.json

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+ ],
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+ "verify": {
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+ "source_sha256": "9671e42ecab91d4c28284a23fcc455ca3c9682f6bfb14c1c6de548a624c234d1",
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+ ],
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+ "mip3d_algorithm": "physical-q-jacobian-colmap-corner-mip3d-unobserved-max.v3",
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FIORD_Hall_In/lidar_alignment.json

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+{
+ "scene": "FIORD_Hall_In",
+ "fiord_folder": "sportunifront",
+ "transform_mesh_to_gt": [
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+ "description": "4x4 similarity transform (row-major) mapping this folder's world frame, shared by mesh/, gaussians*/ and cameras.json, into the frame of the FIORD LiDAR ground truth in metres. The paper's method-independent alignment: the FIORD SfM-to-LiDAR registration refined by a rigid ICP correction that fixes a 3.4 degree tilt, applied identically to every method.",
+ "use": "x_gt = (transform_mesh_to_gt @ [x, 1])[:3]; the paper scores F-score at 10 cm in this frame.",
+ "source_sha256": "77736a601da2c3a741f0265568b9170d14e4db8cc158f7685395d20e43333101"
+}