Refresh Blender indoor metadata after quality replacement

Update frame manifests, scene/frame id mappings, source manifest, README/Croissant, and checksum manifests after the 2026-06-01 replacement upload. The scene data files were uploaded in prior commits; this commit updates metadata only.

README.md

@@ -27,7 +27,7 @@ pretty_name: CM-EVS — Coverage-Curated Panoramic RGB-D Dataset
 
 CM-EVS is a curated panoramic RGB-D dataset built under a single principle: **maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible**. The release is structured as one redistributable Blender indoor data archive plus four license-aware adapter packages that regenerate matched frames locally from upstream sources whose terms forbid redistribution.
 
-> **v1.0 status**: this version stages the **full Blender indoor data drop** (374 scene instances, 13,631 ERP RGB-depth-pose frames; 201 from the round1+2 sampling and 173 from round2). The paper's headline `326 scenes / 11,583 frames` is the curator-selected subset that will be derived from this drop after the §5 evaluation experiments finalize.
+> **v1.0 status**: this version stages the **full Blender indoor data drop** (374 scene instances, 13,631 ERP RGB-depth-pose frames; 201 from the round1+2 sampling and 173 from round2). The paper's headline `326 scenes / 11,583 frames` is the curator-selected subset that will be derived from this drop after the §5 evaluation experiments finalize. See `TODO.md` for items still in flight.
 
 ## Dataset summary
 
@@ -57,7 +57,7 @@ Every released ERP frame follows a single coordinate convention:
 | `panorama_{NNNN}_depth.npy` | float32 array | ERP range depth (m); NaN or 0 if invalid; absent for some frames where depth was not produced |
 | `pose_{NNNN}.json` | JSON | `q_wc`, position, `camera_type` |
 
-Per-scene `meta.json`, `metadata/selected_viewpoints.json`, `metadata/candidates.jsonl`, `metadata/per_step_log.jsonl` (curator-only) will land here once the curator runs on the merged 374-scene set.
+Per-scene `meta.json`, `metadata/selected_viewpoints.json`, `metadata/candidates.jsonl`, `metadata/per_step_log.jsonl` (curator-only) will land here once the curator runs on the merged 374-scene set; see `TODO.md`.
 
 ## Directory layout
 
@@ -68,10 +68,11 @@ cmevs_hf_release/
 ├── CHANGELOG.md
 ├── croissant.json       (MLCommons Croissant v1.0; passes mlcroissant 1.1 validator)
 ├── SHA256SUMS           (top-level checksums, excluding blender_indoor/scenes/)
+├── TODO.md              (pre-push checklist)
 ├── blender_indoor/
 │   ├── README.md
 │   ├── scenes/sence_indoor_{0001..0374}/{panorama,pose}_{NNNN}.{png,npy,json}
-│   ├── SHA256SUMS       (39,896 lines for 13,631 frames × ~3 files)
+│   ├── SHA256SUMS       (40,893 lines for 13,631 RGB-depth-pose files)
 │   └── metadata/{source_manifest.json, splits.json, frame_manifest.csv,
 │                  scene_id_mapping.csv, frame_id_mapping.csv}
 ├── adapters/{hm3d, scannetpp, ob3d, tartanground}/
@@ -97,13 +98,13 @@ Following Gebru et al. 2021. (Source: `main.tex` Appendix A — content here is
 
 **Instances.** Each instance is an ERP frame triple (RGB image + range-depth array + camera pose), plus per-scene `meta.json` and curator-only provenance metadata.
 
-**Counts.** v1.0 stages 13,631 ERP frames across 374 Blender indoor scene instances (CC-BY 4.0). The four restricted sources (HM3D / ScanNet++ / OB3D / TartanGround) ship adapters only; users regenerate matching frames locally.
+**Counts.** v1.0 stages 13,631 ERP RGB-depth-pose frames across 374 Blender indoor scene instances (CC-BY 4.0). A 2026-06-01 quality replacement refreshed 122 Blender indoor scene directories while preserving the release-level scene/frame totals; RGB, depth, and pose counts are now all 13,631. Provenance for replaced scene contents is recorded in `blender_indoor/metadata/scene_id_mapping.csv` and `frame_id_mapping.csv`. The four restricted sources (HM3D / ScanNet++ / OB3D / TartanGround) ship adapters only; users regenerate matching frames locally.
 
 **Sampling.** Indoor (Blender) frames are produced offline by Cycles ERP rendering. The 374 scene instances comprise 201 from round1+2 (Blender_indoor_FOU_threshold-0.2, rounds 1+2 merge) and 173 from round2 (independent extraction). 48 original `sence_indoor_XXXX` ids appear in both rounds with different sampling outcomes; both versions are kept and renumbered (see `blender_indoor/metadata/scene_id_mapping.csv` for traceability). Outdoor source trajectories (TartanGround, OB3D) are re-encoded into the unified schema by the `adapters/{tartanground,ob3d}/` pipelines; the curator does not run on outdoor sources in v1.0.
 
 **Fields.** RGB PNG (2048×1024 for Blender indoor; native source resolution otherwise), float32 range depth (`.npy`), pose JSON with scalar-first `q_wc`, `meta.json`, candidate / viewpoint / per-step-log metadata (curator-produced frames only), source / scene / split ids.
 
-**Missing values.** Invalid depth pixels are NaN or 0 by source convention; per-frame invalid-depth ratio statistics will land in `results/frame_quality.csv` .
+**Missing values.** Invalid depth pixels are NaN or 0 by source convention; per-frame invalid-depth ratio statistics will land in `results/frame_quality.csv` (see TODO).
 
 **Splits.** Default scene-level 70 / 15 / 15 split via `sha256(new_scene_id) % 100`. See `blender_indoor/metadata/splits.json`. The downstream panoramic-depth experiment (paper §4.10) uses a separate 94-scene Blender-indoor subset under its own scene-level split (84 / 10 / 10 = 3,400 / 362 / 423 frames).
 
@@ -170,7 +171,7 @@ Scene directories under `blender_indoor/scenes/` use the legacy id pattern `senc
 # top-level files + adapter packages + code + metadata
 shasum -a 256 -c SHA256SUMS
 
-# Blender indoor frames (39,896 entries: 13,631 panorama + 12,634 depth + 13,631 pose)
+# Blender indoor frames (40,893 entries: 13,631 panorama + 13,631 depth + 13,631 pose)
 cd blender_indoor && shasum -a 256 -c SHA256SUMS
 ```
 

SHA256SUMS

@@ -1,6 +1,6 @@
 335453649489fd3fa08a4296e38ba8a86dabb8455501ad9f78ef2b08a4092bd6  CHANGELOG.md
 6c00f7c8cd699b2e706058cf03f8a12866fb588abebf80a29ba21ff4b4407ac5  LICENSE.md
-a04a8e6d4ce3bf5c9dab3aa27c7e050e08247106dce5b5e7637e5d23ede533c4  README.md
+7594762d6073d07eab676870c2fd68ec11af12930bf2d160a3f33b5f5b25c6a0  README.md
 296be8845dcbe9d09f01762726d5618c62e2adebd530bd1286b9eb342d91ecb3  TODO.md
 2c66395c6714c6664039a03344cb795c9216258b957d16990f020623883ebe48  adapters/README.md
 979bb0b0eba729b79f2f1b1fa51095d8a58ca6d363abc6dc7e678c8517d90c61  adapters/hm3d/README.md
@@ -19,11 +19,11 @@ f7d2598f886e92d8d197d54fbc5daffa6851cfa00b09a7746be07ca3b1ae7e5f  adapters/tarta
 4685882bc25d76b6cf1d1edbc142687f1d3165864a50267cfc245340bac8c948  adapters/tartanground/config.yaml
 7d7f2208aac42acfeee05dc6e0683b1a9f81aabbc66c58c7f1cb6ad0547b1aa5  adapters/tartanground/metadata/source_manifest.json
 8dc66b506fdd7f5a2f093e32ed90c9c203b5884c301f9be2afe83831e2862f8a  adapters/tartanground/reencoding_script.md
-cce8650483e0e6b80ff5872ce954d1e4db639a6a6bdfb0dacfe9fa003818aafc  blender_indoor/README.md
-8a61d8ea13c49e66394810776f982ae5918e43ecd9c5482796801a1355a551bb  blender_indoor/metadata/frame_id_mapping.csv
-6d851b67947c8e9d2992b4fbb935db4b6cebab7ce917b0e03242d8f6e3e94c4d  blender_indoor/metadata/frame_manifest.csv
-58f2ee4949e5def251babc54f39bf9ee170d482a116d0a337993726f7b565c92  blender_indoor/metadata/scene_id_mapping.csv
-c44fabb3932d6067704825d9af59ccf633c5129bffad9fd8a30ed4720a726ae1  blender_indoor/metadata/source_manifest.json
+4666091d7c612e24bec84fa95b7495bc412c6567ad8f21b084d46707243949b4  blender_indoor/README.md
+ad824ef9cfe0a623196a6fff4558a55e5ae4f77fc8e841425ea3a4e22aae1132  blender_indoor/metadata/frame_id_mapping.csv
+c1bfd6220ae0b8155e281c3cb23b78e009437dd0ee208721e216b0a12d31556f  blender_indoor/metadata/frame_manifest.csv
+10e5ba64134fc22e82f27838514852f58c6b2b74c7932cf8ba6a83b960dfbc1c  blender_indoor/metadata/scene_id_mapping.csv
+b60c4375bf290d41fda8fdce6aa648da0aecbd036ed3d8102b480557ae3d7a05  blender_indoor/metadata/source_manifest.json
 072493c9e533554c0faafb1d3ba766365152f6c5084e2837d29f4d5279c76ab6  blender_indoor/metadata/splits.json
 2c14d7ac4ef207357073eabef1bc7f65853ab248237550a5542a59ba677f8ade  code/LICENSE
 b8bba6d5adc75decd73c4da0723b60c2678bb94985ba07085b08dc391faa0e35  code/README.md
@@ -43,7 +43,7 @@ ee596d36829271f164a4e1d6a297aaa42ef8eaaa0339d3b4b14f3b9089b084c7  code/core/erp_
 f714d3d887b142cb63f0c1fc23dde0949b1e179330964edb6216bc06d5d318ab  code/core/erp_warp.py
 a8a1ba38ffde69fd0c07f653fc388dc9fc53eb5aa2b95a3ed58d54848714e03e  code/core/tangent_extraction.py
 21e7c6c68fd31d5c63f6cb9f949e38adf78a5660f83650481afccc418b9390ab  code/data/README.md
-e5261ad1221380fad1174aeb931355679f419f8bfa8266f3bff06d9b2b917f75  code/dataset_metadata/croissant.json
+bab2043e5a3e79272c8155ba7999db5a119f6249de92f2f4b8f9b0718d3b2932  code/dataset_metadata/croissant.json
 c9e7127fc7c6de554516ee219e8aeaa2fca1b00951099d973c7e8af8db32ea95  code/environment.yml
 4b6766691ae074a066ed06919cc372a2849b435e372e6a24849154d0b09c1195  code/examples/metadata/candidates.jsonl
 71c290335857fd7b4a53e507bc94fa6e6c20d1fbdc768fed0e9de20e11229e65  code/examples/tiny_blender_scene/README.md
@@ -78,7 +78,7 @@ e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855  code/tools/__i
 1f28cb01c320379ce4138842f848fdcae2db224b805942d0e17c20d132c74609  code/tools/navmesh_utils.py
 08dc49bc2f8bf272274625235f7a9eeec99f94bb3e011778731cc87f28157552  code/tools/semantic_utils.py
 80b87f28df042b2789fd650aec2bbf97a29b6d3a20bb2b13b7dba3c64ec8e06a  code/tools/update_croissant_with_real_hashes.py
-e5261ad1221380fad1174aeb931355679f419f8bfa8266f3bff06d9b2b917f75  croissant.json
+bab2043e5a3e79272c8155ba7999db5a119f6249de92f2f4b8f9b0718d3b2932  croissant.json
 776469105fec88931d5d91239f98b31284e7e090beaf8a8bd7f4aa2e03728594  results/README.md
 df494f4c0a6fc76d9180310286f839e6c4631c009b0244ea192eb552b186c50f  results/audit_50_frames.csv
 04d0f1d19756fb279564a4d5ba0e571f2cab8518a50cce4860d292065bfa64c2  results/coverage_main.csv

blender_indoor/README.md

@@ -1,6 +1,6 @@
 # Blender indoor — CM-EVS v1.0
 
-374 scene instances, 13,631 ERP RGB frames, 12,634 range-depth NumPy arrays, 13,631 pose JSON files. Resolution **2048×1024**. Released under **CC-BY 4.0**.
+374 scene instances, 13,631 ERP RGB frames, 13,631 range-depth NumPy arrays, 13,631 pose JSON files. Resolution **2048×1024**. Released under **CC-BY 4.0**.
 
 This is the only redistributable RGB-D portion of CM-EVS. The four restricted sources (HM3D, ScanNet++, OB3D, TartanGround) ship adapter code only — see `../adapters/`.
 
@@ -9,7 +9,7 @@ This is the only redistributable RGB-D portion of CM-EVS. The four restricted so
 ```
 blender_indoor/
 ├── README.md                   (this file)
-├── SHA256SUMS                  (39,896 lines covering every panorama, depth, pose)
+├── SHA256SUMS                  (40,893 lines covering every panorama, depth, pose)
 ├── scenes/
 │   ├── sence_indoor_0001/      (← from round1+2, original sence_indoor_0001)
 │   │   ├── panorama_0000.png
@@ -77,14 +77,14 @@ Once the curator runs on the merged 374-scene set, each scene will additionally
 - `metadata/candidates.jsonl` — feasible candidates with 26-direction validity flags
 - `metadata/per_step_log.jsonl` — per-step `G_t`, `L_t`, `s_t`, runtime
 
-These are documented in paper §4.1 Table.
+These are documented in paper §4.1 Table; tracked under `TODO.md`.
 
 ## Verifying integrity
 
 ```bash
 cd blender_indoor
 shasum -a 256 -c SHA256SUMS
-# 39,896 / 39,896 should pass
+# 40,893 / 40,893 should pass
 ```
 
 ## License

blender_indoor/metadata/scene_id_mapping.csv

@@ -1,5 +1,5 @@
 new_scene_id,source_round,original_scene_id,frame_count
-sence_indoor_0001,round1+2,sence_indoor_0001,33
+sence_indoor_0001,round1+2,sence_indoor_0001,31
 sence_indoor_0002,round1+2,sence_indoor_0002,33
 sence_indoor_0003,round1+2,sence_indoor_0003,29
 sence_indoor_0004,round1+2,sence_indoor_0004,29
@@ -7,30 +7,30 @@ sence_indoor_0005,round1+2,sence_indoor_0005,33
 sence_indoor_0006,round1+2,sence_indoor_0005-第二轮,47
 sence_indoor_0007,round1+2,sence_indoor_0007,12
 sence_indoor_0008,round1+2,sence_indoor_0008,53
-sence_indoor_0009,round1+2,sence_indoor_0009,23
+sence_indoor_0009,round1+2,sence_indoor_0009,14
 sence_indoor_0010,round1+2,sence_indoor_0012,53
 sence_indoor_0011,round1+2,sence_indoor_0013,53
-sence_indoor_0012,round1+2,sence_indoor_0014,33
+sence_indoor_0012,quality_replacement_2026-06-01:round1,sence_indoor_0010,35
 sence_indoor_0013,round1+2,sence_indoor_0015,33
-sence_indoor_0014,round1+2,sence_indoor_0016,35
-sence_indoor_0015,round1+2,sence_indoor_0018,33
-sence_indoor_0016,round1+2,sence_indoor_0018-第二轮,15
+sence_indoor_0014,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0010,48
+sence_indoor_0015,round1+2,sence_indoor_0018,30
+sence_indoor_0016,round1+2,sence_indoor_0018-第二轮,10
 sence_indoor_0017,round1+2,sence_indoor_0019,33
 sence_indoor_0018,round1+2,sence_indoor_0020,33
 sence_indoor_0019,round1+2,sence_indoor_0021,21
-sence_indoor_0020,round1+2,sence_indoor_0021-第二轮,31
-sence_indoor_0021,round1+2,sence_indoor_0023,16
-sence_indoor_0022,round1+2,sence_indoor_0024,53
-sence_indoor_0023,round1+2,sence_indoor_0027,29
-sence_indoor_0024,round1+2,sence_indoor_0028,21
-sence_indoor_0025,round1+2,sence_indoor_0030,22
+sence_indoor_0020,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0039,16
+sence_indoor_0021,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0045,9
+sence_indoor_0022,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0072,28
+sence_indoor_0023,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0074,30
+sence_indoor_0024,quality_replacement_2026-06-01:round1,sence_indoor_0012,51
+sence_indoor_0025,quality_replacement_2026-06-01:round1,sence_indoor_0017,16
 sence_indoor_0026,round1+2,sence_indoor_0031,7
-sence_indoor_0027,round1+2,sence_indoor_0036,23
-sence_indoor_0028,round1+2,sence_indoor_0036-第二轮,53
+sence_indoor_0027,round1+2,sence_indoor_0036,17
+sence_indoor_0028,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0092,27
 sence_indoor_0029,round1+2,sence_indoor_0037,53
-sence_indoor_0030,round1+2,sence_indoor_0038,29
+sence_indoor_0030,quality_replacement_2026-06-01:round1,sence_indoor_0024,43
 sence_indoor_0031,round1+2,sence_indoor_0040,48
-sence_indoor_0032,round1+2,sence_indoor_0041,29
+sence_indoor_0032,quality_replacement_2026-06-01:round1,sence_indoor_0035,36
 sence_indoor_0033,round1+2,sence_indoor_0041-第二轮,12
 sence_indoor_0034,round1+2,sence_indoor_0043,53
 sence_indoor_0035,round1+2,sence_indoor_0044,33
@@ -40,15 +40,15 @@ sence_indoor_0038,round1+2,sence_indoor_0050,53
 sence_indoor_0039,round1+2,sence_indoor_0051,21
 sence_indoor_0040,round1+2,sence_indoor_0054,15
 sence_indoor_0041,round1+2,sence_indoor_0057,25
-sence_indoor_0042,round1+2,sence_indoor_0058,23
-sence_indoor_0043,round1+2,sence_indoor_0060,29
+sence_indoor_0042,quality_replacement_2026-06-01:round1,sence_indoor_0036,33
+sence_indoor_0043,quality_replacement_2026-06-01:round1,sence_indoor_0047,97
 sence_indoor_0044,round1+2,sence_indoor_0067,9
 sence_indoor_0045,round1+2,sence_indoor_0069,15
 sence_indoor_0046,round1+2,sence_indoor_0070,53
 sence_indoor_0047,round1+2,sence_indoor_0071,33
 sence_indoor_0048,round1+2,sence_indoor_0072,52
 sence_indoor_0049,round1+2,sence_indoor_0074,25
-sence_indoor_0050,round1+2,sence_indoor_0074-第二轮,26
+sence_indoor_0050,round1+2,sence_indoor_0074-第二轮,24
 sence_indoor_0051,round1+2,sence_indoor_0075,17
 sence_indoor_0052,round1+2,sence_indoor_0076,33
 sence_indoor_0053,round1+2,sence_indoor_0076-第二轮,17
@@ -58,22 +58,22 @@ sence_indoor_0056,round1+2,sence_indoor_0084,53
 sence_indoor_0057,round1+2,sence_indoor_0085,53
 sence_indoor_0058,round1+2,sence_indoor_0086,53
 sence_indoor_0059,round1+2,sence_indoor_0088,33
-sence_indoor_0060,round1+2,sence_indoor_0089,23
-sence_indoor_0061,round1+2,sence_indoor_0091,17
-sence_indoor_0062,round1+2,sence_indoor_0092,33
+sence_indoor_0060,quality_replacement_2026-06-01:round1,sence_indoor_0049,47
+sence_indoor_0061,round1+2,sence_indoor_0091,16
+sence_indoor_0062,round1+2,sence_indoor_0092,17
 sence_indoor_0063,round1+2,sence_indoor_0092-第二轮,53
-sence_indoor_0064,round1+2,sence_indoor_0094,9
+sence_indoor_0064,quality_replacement_2026-06-01:round1,sence_indoor_0059,25
 sence_indoor_0065,round1+2,sence_indoor_0094-第二轮,46
-sence_indoor_0066,round1+2,sence_indoor_0095,33
-sence_indoor_0067,round1+2,sence_indoor_0096,30
+sence_indoor_0066,quality_replacement_2026-06-01:round1,sence_indoor_0065,47
+sence_indoor_0067,quality_replacement_2026-06-01:round1,sence_indoor_0081,11
 sence_indoor_0068,round1+2,sence_indoor_0098,52
-sence_indoor_0069,round1+2,sence_indoor_0100,33
+sence_indoor_0069,quality_replacement_2026-06-01:round1,sence_indoor_0086,36
 sence_indoor_0070,round1+2,sence_indoor_0100-第二轮,53
-sence_indoor_0071,round1+2,sence_indoor_0102,22
+sence_indoor_0071,quality_replacement_2026-06-01:round1,sence_indoor_0087,51
 sence_indoor_0072,round1+2,sence_indoor_0104,33
-sence_indoor_0073,round1+2,sence_indoor_0105,33
+sence_indoor_0073,quality_replacement_2026-06-01:round1,sence_indoor_0101,44
 sence_indoor_0074,round1+2,sence_indoor_0106,33
-sence_indoor_0075,round1+2,sence_indoor_0108,53
+sence_indoor_0075,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0106,4
 sence_indoor_0076,round1+2,sence_indoor_0111,33
 sence_indoor_0077,round1+2,sence_indoor_0111-第二轮,12
 sence_indoor_0078,round1+2,sence_indoor_0112,33
@@ -83,25 +83,25 @@ sence_indoor_0081,round1+2,sence_indoor_0114,33
 sence_indoor_0082,round1+2,sence_indoor_0116,53
 sence_indoor_0083,round1+2,sence_indoor_0122,33
 sence_indoor_0084,round1+2,sence_indoor_0123,52
-sence_indoor_0085,round1+2,sence_indoor_0124,33
+sence_indoor_0085,round1+2,sence_indoor_0124,21
 sence_indoor_0086,round1+2,sence_indoor_0124-第二轮,49
 sence_indoor_0087,round1+2,sence_indoor_0125,53
 sence_indoor_0088,round1+2,sence_indoor_0127,29
 sence_indoor_0089,round1+2,sence_indoor_0128,33
-sence_indoor_0090,round1+2,sence_indoor_0128-第二轮,16
-sence_indoor_0091,round1+2,sence_indoor_0129,53
+sence_indoor_0090,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0113,3
+sence_indoor_0091,quality_replacement_2026-06-01:hf_local_good_scene,sence_indoor_0122,47
 sence_indoor_0092,round1+2,sence_indoor_0131,33
 sence_indoor_0093,round1+2,sence_indoor_0132,33
 sence_indoor_0094,round1+2,sence_indoor_0132-第二轮,7
 sence_indoor_0095,round1+2,sence_indoor_0134,33
 sence_indoor_0096,round1+2,sence_indoor_0135,13
 sence_indoor_0097,round1+2,sence_indoor_0135-第二轮,53
-sence_indoor_0098,round1+2,sence_indoor_0137,53
-sence_indoor_0099,round1+2,sence_indoor_0138,29
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 sence_indoor_0100,round1+2,sence_indoor_0139,33
 sence_indoor_0101,round1+2,sence_indoor_0139-第二轮,15
 sence_indoor_0102,round1+2,sence_indoor_0140,29
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 sence_indoor_0104,round1+2,sence_indoor_0142,33
 sence_indoor_0105,round1+2,sence_indoor_0144,25
 sence_indoor_0106,round1+2,sence_indoor_0145,13
@@ -112,23 +112,23 @@ sence_indoor_0110,round1+2,sence_indoor_0155,30
 sence_indoor_0111,round1+2,sence_indoor_0156,53
 sence_indoor_0112,round1+2,sence_indoor_0165-第二轮,53
 sence_indoor_0113,round1+2,sence_indoor_0169,9
-sence_indoor_0114,round1+2,sence_indoor_0169-第二轮,53
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 sence_indoor_0115,round1+2,sence_indoor_0170,21
 sence_indoor_0116,round1+2,sence_indoor_0170-第二轮,51
 sence_indoor_0117,round1+2,sence_indoor_0172,36
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 sence_indoor_0119,round1+2,sence_indoor_0174,29
 sence_indoor_0120,round1+2,sence_indoor_0175,29
 sence_indoor_0121,round1+2,sence_indoor_0177,13
 sence_indoor_0122,round1+2,sence_indoor_0177-第二轮,53
-sence_indoor_0123,round1+2,sence_indoor_0180,27
+sence_indoor_0123,round1+2,sence_indoor_0180,20
 sence_indoor_0124,round1+2,sence_indoor_0181,47
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 sence_indoor_0126,round1+2,sence_indoor_0184,53
 sence_indoor_0127,round1+2,sence_indoor_0192,48
 sence_indoor_0128,round1+2,sence_indoor_0193,33
 sence_indoor_0129,round1+2,sence_indoor_0194,24
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 sence_indoor_0131,round1+2,sence_indoor_0230,14
 sence_indoor_0132,round1+2,sence_indoor_0234,30
 sence_indoor_0133,round1+2,sence_indoor_0238,33
@@ -136,11 +136,11 @@ sence_indoor_0134,round1+2,sence_indoor_0239,33
 sence_indoor_0135,round1+2,sence_indoor_0245,29
 sence_indoor_0136,round1+2,sence_indoor_0248,33
 sence_indoor_0137,round1+2,sence_indoor_0252,33
-sence_indoor_0138,round1+2,sence_indoor_0255,33
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 sence_indoor_0139,round1+2,sence_indoor_0260,29
 sence_indoor_0140,round1+2,sence_indoor_0264,26
 sence_indoor_0141,round1+2,sence_indoor_0266,29
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 sence_indoor_0143,round1+2,sence_indoor_0268,32
 sence_indoor_0144,round1+2,sence_indoor_0269,29
 sence_indoor_0145,round1+2,sence_indoor_0270,29
@@ -148,37 +148,37 @@ sence_indoor_0146,round1+2,sence_indoor_0271,28
 sence_indoor_0147,round1+2,sence_indoor_0276,33
 sence_indoor_0148,round1+2,sence_indoor_0277,25
 sence_indoor_0149,round1+2,sence_indoor_0284,33
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 sence_indoor_0151,round1+2,sence_indoor_0290,33
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 sence_indoor_0155,round1+2,sence_indoor_0296,33
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 sence_indoor_0165,round1+2,sence_indoor_0315,33
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 sence_indoor_0168,round1+2,sence_indoor_0319,22
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 sence_indoor_0175,round1+2,sence_indoor_0328,19
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 sence_indoor_0178,round1+2,sence_indoor_0331,47
 sence_indoor_0179,round1+2,sence_indoor_0334,53
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 sence_indoor_0181,round1+2,sence_indoor_0339,40
 sence_indoor_0182,round1+2,sence_indoor_0341,26
 sence_indoor_0183,round1+2,sence_indoor_0343,51
@@ -187,7 +187,7 @@ sence_indoor_0185,round1+2,sence_indoor_0349,34
 sence_indoor_0186,round1+2,sence_indoor_0350,53
 sence_indoor_0187,round1+2,sence_indoor_0355,33
 sence_indoor_0188,round1+2,sence_indoor_0358,33
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 sence_indoor_0190,round1+2,sence_indoor_0362,29
 sence_indoor_0191,round1+2,sence_indoor_0364,19
 sence_indoor_0192,round1+2,sence_indoor_0365,33
@@ -196,21 +196,21 @@ sence_indoor_0194,round1+2,sence_indoor_0377,31
 sence_indoor_0195,round1+2,sence_indoor_0379,33
 sence_indoor_0196,round1+2,sence_indoor_0381,33
 sence_indoor_0197,round1+2,sence_indoor_0382,33
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 sence_indoor_0207,round2,sence_indoor_0030,53
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 sence_indoor_0209,round2,sence_indoor_0033,48
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 sence_indoor_0214,round2,sence_indoor_0047,44
 sence_indoor_0215,round2,sence_indoor_0051,53
@@ -220,11 +220,11 @@ sence_indoor_0218,round2,sence_indoor_0065,51
 sence_indoor_0219,round2,sence_indoor_0073,20
 sence_indoor_0220,round2,sence_indoor_0081,53
 sence_indoor_0221,round2,sence_indoor_0087,53
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 sence_indoor_0223,round2,sence_indoor_0090,14
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 sence_indoor_0228,round2,sence_indoor_0102,53
 sence_indoor_0229,round2,sence_indoor_0103,39
@@ -237,13 +237,13 @@ sence_indoor_0235,round2,sence_indoor_0119,50
 sence_indoor_0236,round2,sence_indoor_0120,43
 sence_indoor_0237,round2,sence_indoor_0126,51
 sence_indoor_0238,round2,sence_indoor_0131,49
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 sence_indoor_0247,round2,sence_indoor_0164,53
 sence_indoor_0248,round2,sence_indoor_0166,53
@@ -253,123 +253,123 @@ sence_indoor_0251,round2,sence_indoor_0182,33
 sence_indoor_0252,round2,sence_indoor_0187,50
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+sence_indoor_0309,round2,sence_indoor_0256,45
+sence_indoor_0310,quality_replacement_2026-06-01:round2,sence_indoor_0155,24
+sence_indoor_0311,quality_replacement_2026-06-01:round2,sence_indoor_0156,52
 sence_indoor_0312,round2,sence_indoor_0260,45
-sence_indoor_0313,round2,sence_indoor_0261,3
-sence_indoor_0314,round2,sence_indoor_0262,37
+sence_indoor_0313,quality_replacement_2026-06-01:round2,sence_indoor_0165,48
+sence_indoor_0314,quality_replacement_2026-06-01:round2,sence_indoor_0169,48
 sence_indoor_0315,round2,sence_indoor_0263,53
-sence_indoor_0316,round2,sence_indoor_0264,53
+sence_indoor_0316,round2,sence_indoor_0264,52
 sence_indoor_0317,round2,sence_indoor_0265,48
 sence_indoor_0318,round2,sence_indoor_0266,53
-sence_indoor_0319,round2,sence_indoor_0268,49
-sence_indoor_0320,round2,sence_indoor_0269,1
-sence_indoor_0321,round2,sence_indoor_0270,53
-sence_indoor_0322,round2,sence_indoor_0271,16
+sence_indoor_0319,quality_replacement_2026-06-01:round2,sence_indoor_0170,48
+sence_indoor_0320,quality_replacement_2026-06-01:round2,sence_indoor_0172,14
+sence_indoor_0321,round2,sence_indoor_0270,45
+sence_indoor_0322,round2,sence_indoor_0271,14
 sence_indoor_0323,round2,sence_indoor_0272,29
-sence_indoor_0324,round2,sence_indoor_0273,4
-sence_indoor_0325,round2,sence_indoor_0274,14
-sence_indoor_0326,round2,sence_indoor_0275,53
-sence_indoor_0327,round2,sence_indoor_0276,53
-sence_indoor_0328,round2,sence_indoor_0277,53
+sence_indoor_0324,quality_replacement_2026-06-01:round2,sence_indoor_0177,48
+sence_indoor_0325,quality_replacement_2026-06-01:round2,sence_indoor_0181,44
+sence_indoor_0326,quality_replacement_2026-06-01:round2,sence_indoor_0184,47
+sence_indoor_0327,quality_replacement_2026-06-01:round2,sence_indoor_0192,37
+sence_indoor_0328,quality_replacement_2026-06-01:round2,sence_indoor_0331,31
 sence_indoor_0329,round2,sence_indoor_0278,53
 sence_indoor_0330,round2,sence_indoor_0279,53
-sence_indoor_0331,round2,sence_indoor_0280,15
+sence_indoor_0331,quality_replacement_2026-06-01:round2,sence_indoor_0334,46
 sence_indoor_0332,round2,sence_indoor_0281,53
-sence_indoor_0333,round2,sence_indoor_0282,53
-sence_indoor_0334,round2,sence_indoor_0283,53
+sence_indoor_0333,quality_replacement_2026-06-01:round2,sence_indoor_0343,24
+sence_indoor_0334,quality_replacement_2026-06-01:round2,sence_indoor_0347,51
 sence_indoor_0335,round2,sence_indoor_0284,53
 sence_indoor_0336,round2,sence_indoor_0286,53
 sence_indoor_0337,round2,sence_indoor_0287,53
-sence_indoor_0338,round2,sence_indoor_0288,53
-sence_indoor_0339,round2,sence_indoor_0289,14
-sence_indoor_0340,round2,sence_indoor_0290,2
-sence_indoor_0341,round2,sence_indoor_0291,5
-sence_indoor_0342,round2,sence_indoor_0292,53
+sence_indoor_0338,quality_replacement_2026-06-01:round2,sence_indoor_0349,27
+sence_indoor_0339,quality_replacement_2026-06-01:round2,sence_indoor_0350,47
+sence_indoor_0340,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0177,47
+sence_indoor_0341,quality_replacement_2026-06-01:round1:random_copy,sence_indoor_0167,42
+sence_indoor_0342,round2,sence_indoor_0292,48
 sence_indoor_0343,round2,sence_indoor_0293,37
-sence_indoor_0344,round2,sence_indoor_0294,53
-sence_indoor_0345,round2,sence_indoor_0297,53
-sence_indoor_0346,round2,sence_indoor_0299,53
-sence_indoor_0347,round2,sence_indoor_0300,1
+sence_indoor_0344,round2,sence_indoor_0294,52
+sence_indoor_0345,quality_replacement_2026-06-01:round1:random_copy,sence_indoor_0203,47
+sence_indoor_0346,round2,sence_indoor_0299,45
+sence_indoor_0347,quality_replacement_2026-06-01:round1:random_copy,sence_indoor_0154,47
 sence_indoor_0348,round2,sence_indoor_0301,53
-sence_indoor_0349,round2,sence_indoor_0303,53
-sence_indoor_0350,round2,sence_indoor_0304,53
+sence_indoor_0349,quality_replacement_2026-06-01:round1:random_copy,sence_indoor_0081,12
+sence_indoor_0350,quality_replacement_2026-06-01:round1:random_copy,sence_indoor_0137,35
 sence_indoor_0351,round2,sence_indoor_0306,53
 sence_indoor_0352,round2,sence_indoor_0307,53
-sence_indoor_0353,round2,sence_indoor_0308,53
+sence_indoor_0353,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0331,30
 sence_indoor_0354,round2,sence_indoor_0310,53
-sence_indoor_0355,round2,sence_indoor_0311,53
-sence_indoor_0356,round2,sence_indoor_0312,53
-sence_indoor_0357,round2,sence_indoor_0313,2
+sence_indoor_0355,quality_replacement_2026-06-01:round1:random_copy,sence_indoor_0147,13
+sence_indoor_0356,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0125,44
+sence_indoor_0357,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0123,12
 sence_indoor_0358,round2,sence_indoor_0314,53
-sence_indoor_0359,round2,sence_indoor_0315,6
+sence_indoor_0359,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0040,29
 sence_indoor_0360,round2,sence_indoor_0316,53
 sence_indoor_0361,round2,sence_indoor_0318,53
 sence_indoor_0362,round2,sence_indoor_0319,53
-sence_indoor_0363,round2,sence_indoor_0321,53
+sence_indoor_0363,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0107,51
 sence_indoor_0364,round2,sence_indoor_0323,53
-sence_indoor_0365,round2,sence_indoor_0324,20
-sence_indoor_0366,round2,sence_indoor_0326,53
+sence_indoor_0365,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0084,48
+sence_indoor_0366,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0005,43
 sence_indoor_0367,round2,sence_indoor_0328,53
-sence_indoor_0368,round2,sence_indoor_0332,28
+sence_indoor_0368,quality_replacement_2026-06-01:round2:random_copy,sence_indoor_0153,25
 sence_indoor_0369,round2,sence_indoor_0333,26
 sence_indoor_0370,round2,sence_indoor_0338,13
 sence_indoor_0371,round2,sence_indoor_0340,51
-sence_indoor_0372,round2,sence_indoor_0342,31
+sence_indoor_0372,round2,sence_indoor_0342,30
 sence_indoor_0373,round2,sence_indoor_0344,45
 sence_indoor_0374,round2,sence_indoor_0346,41

blender_indoor/metadata/source_manifest.json

@@ -3,16 +3,49 @@
   "license": "CC-BY-4.0",
   "scene_count": 374,
   "frame_count": 13631,
+  "file_counts": {
+    "rgb_png": 13631,
+    "depth_npy": 13631,
+    "pose_json": 13631
+  },
   "rounds": {
+    "quality_replacement_2026-06-01:hf_local_good_scene": {
+      "scene_count": 23,
+      "frame_count": 734
+    },
+    "quality_replacement_2026-06-01:round1": {
+      "scene_count": 32,
+      "frame_count": 1242
+    },
+    "quality_replacement_2026-06-01:round1:random_copy": {
+      "scene_count": 6,
+      "frame_count": 196
+    },
+    "quality_replacement_2026-06-01:round2": {
+      "scene_count": 52,
+      "frame_count": 1850
+    },
+    "quality_replacement_2026-06-01:round2:random_copy": {
+      "scene_count": 9,
+      "frame_count": 329
+    },
     "round1+2": {
-      "scene_count": 201,
-      "frame_count": 6740
+      "scene_count": 155,
+      "frame_count": 5001
     },
     "round2": {
-      "scene_count": 173,
-      "frame_count": 6891
+      "scene_count": 97,
+      "frame_count": 4279
     }
   },
+  "quality_replacement": {
+    "date": "2026-06-01",
+    "replaced_scene_count": 122,
+    "replaced_frame_count": 4351,
+    "annotation_file": "quality_annotations.json",
+    "mapping_file": "replacement_rename_to_quality_annotations_bad_scenes.csv",
+    "note": "122 low-quality or missing-depth scene directories were removed and re-uploaded under the same scene ids. See scene_id_mapping.csv and frame_id_mapping.csv for replacement provenance."
+  },
   "scene_id_range": [
     "sence_indoor_0001",
     "sence_indoor_0374"

code/dataset_metadata/croissant.json

@@ -51,7 +51,7 @@
   "description": "CM-EVS is a curated panoramic RGB-D dataset built under a single principle: maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible. The headline release contains 11,583 ERP RGB-depth-pose frames over 326 Blender indoor scenes (CC-BY 4.0), each paired with the per-step provenance log of the depth-conflict-aware curator that selected it. The full v1.0 release additionally provides 786,344 frames re-encoded from TartanGround (783,944 frames over 63 environments) and OB3D (2,400 frames over 12 scenes) outdoor sources into the same ERP and world-to-camera pose schema, plus license-aware adapter packages for HM3D (14,475 frames over 401 rooms after local regeneration) and ScanNet++ (8,267 frames over 500 scans after local regeneration) that produce matched frames locally without redistributing licensed assets.",
   "version": "1.0.0",
   "license": "https://creativecommons.org/licenses/by/4.0/",
-  "url": "https://anonymous.4open.science/r/cmevs-XXXX",
+  "url": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval",
   "citeAs": "@inproceedings{cmevs2026, title={{CM-EVS}: A Coverage-Curated Panoramic {RGB-D} Dataset for Indoor Scene Understanding}, author={Anonymous Author(s)}, booktitle={NeurIPS 2026 Datasets and Benchmarks Track (under review)}, year={2026}}",
   "creator": {
     "@type": "Organization",
@@ -78,7 +78,7 @@
       "@type": "cr:FileObject",
       "@id": "blender-indoor-archive.tar",
       "name": "blender-indoor-archive.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/blender_indoor.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -86,7 +86,9 @@
       "@type": "cr:FileSet",
       "@id": "blender-indoor-rgb",
       "name": "blender-indoor-rgb",
-      "containedIn": {"@id": "blender-indoor-archive.tar"},
+      "containedIn": {
+        "@id": "blender-indoor-archive.tar"
+      },
       "encodingFormat": "image/png",
       "includes": "rgb/*.png"
     },
@@ -94,7 +96,9 @@
       "@type": "cr:FileSet",
       "@id": "blender-indoor-depth",
       "name": "blender-indoor-depth",
-      "containedIn": {"@id": "blender-indoor-archive.tar"},
+      "containedIn": {
+        "@id": "blender-indoor-archive.tar"
+      },
       "encodingFormat": "application/octet-stream",
       "includes": "depth/*.npy"
     },
@@ -102,7 +106,9 @@
       "@type": "cr:FileSet",
       "@id": "blender-indoor-pose",
       "name": "blender-indoor-pose",
-      "containedIn": {"@id": "blender-indoor-archive.tar"},
+      "containedIn": {
+        "@id": "blender-indoor-archive.tar"
+      },
       "encodingFormat": "application/json",
       "includes": "pose/*.json"
     },
@@ -110,7 +116,9 @@
       "@type": "cr:FileSet",
       "@id": "blender-indoor-metadata",
       "name": "blender-indoor-metadata",
-      "containedIn": {"@id": "blender-indoor-archive.tar"},
+      "containedIn": {
+        "@id": "blender-indoor-archive.tar"
+      },
       "encodingFormat": "application/json",
       "includes": "metadata/*.json*"
     },
@@ -118,7 +126,7 @@
       "@type": "cr:FileObject",
       "@id": "outdoor-tartanground-adapter.tar",
       "name": "outdoor-tartanground-adapter.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/outdoor_tartanground_adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/outdoor_tartanground_adapter.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -126,7 +134,7 @@
       "@type": "cr:FileObject",
       "@id": "outdoor-ob3d-adapter.tar",
       "name": "outdoor-ob3d-adapter.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/outdoor_ob3d_adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/outdoor_ob3d_adapter.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -134,7 +142,7 @@
       "@type": "cr:FileObject",
       "@id": "hm3d-adapter.tar",
       "name": "hm3d-adapter.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/hm3d_adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/hm3d_adapter.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -142,7 +150,7 @@
       "@type": "cr:FileObject",
       "@id": "scannetpp-adapter.tar",
       "name": "scannetpp-adapter.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/scannetpp_adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/scannetpp_adapter.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -150,7 +158,7 @@
       "@type": "cr:FileObject",
       "@id": "curator-source-code.tar",
       "name": "curator-source-code.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/code.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/code.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -158,7 +166,7 @@
       "@type": "cr:FileObject",
       "@id": "documentation.tar",
       "name": "documentation.tar",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/docs.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/docs.tar",
       "encodingFormat": "application/x-tar",
       "sha256": "TODO_SHA256"
     },
@@ -166,9 +174,9 @@
       "@type": "cr:FileObject",
       "@id": "frame-manifest.csv",
       "name": "frame-manifest.csv",
-      "contentUrl": "https://anonymous.4open.science/r/cmevs-XXXX/frame_manifest.csv",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/metadata/frame_manifest.csv",
       "encodingFormat": "text/csv",
-      "sha256": "TODO_SHA256"
+      "sha256": "c1bfd6220ae0b8155e281c3cb23b78e009437dd0ee208721e216b0a12d31556f"
     }
   ],
   "recordSet": [
@@ -183,98 +191,196 @@
           "@id": "erp-frame-records/frame_id",
           "name": "frame_id",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "frame_id"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "frame_id"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/source",
           "name": "source",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "source"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "source"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/scene_id",
           "name": "scene_id",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "scene_id"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "scene_id"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/room_id",
           "name": "room_id",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "room_id"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "room_id"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/split",
           "name": "split",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "split"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "split"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/rgb",
           "name": "rgb",
           "dataType": "sc:ImageObject",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "rgb_path"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "rgb_path"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/depth",
           "name": "depth",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "depth_path"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "depth_path"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/pose_quaternion",
           "name": "pose_quaternion",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "pose_quaternion"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "pose_quaternion"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/pose_position",
           "name": "pose_position",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "pose_position"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "pose_position"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/camera_type",
           "name": "camera_type",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "camera_type"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "camera_type"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/viewpoint_score",
           "name": "viewpoint_score",
           "dataType": "sc:Float",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "viewpoint_score"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "viewpoint_score"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/coverage_gain",
           "name": "coverage_gain",
           "dataType": "sc:Float",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "coverage_gain"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "coverage_gain"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/conflict_ratio",
           "name": "conflict_ratio",
           "dataType": "sc:Float",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "conflict_ratio"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "conflict_ratio"
+            }
+          }
         },
         {
           "@type": "cr:Field",
           "@id": "erp-frame-records/candidate_id",
           "name": "candidate_id",
           "dataType": "sc:Text",
-          "source": {"fileObject": {"@id": "frame-manifest.csv"}, "extract": {"column": "candidate_id"}}
+          "source": {
+            "fileObject": {
+              "@id": "frame-manifest.csv"
+            },
+            "extract": {
+              "column": "candidate_id"
+            }
+          }
         }
       ]
     }

croissant.json

@@ -48,8 +48,8 @@
   "@type": "sc:Dataset",
   "conformsTo": "http://mlcommons.org/croissant/1.0",
   "name": "CM-EVS",
-  "description": "CM-EVS is a curated panoramic RGB-D dataset built under a single principle: maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible. The headline release contains 13,631 ERP RGB-depth-pose frames over 374 Blender indoor scenes (CC-BY 4.0), each paired with the per-step provenance log of the depth-conflict-aware curator that selected it. The full v1.0 release additionally provides 786,344 frames re-encoded from TartanGround (783,944 frames over 63 environments) and OB3D (2,400 frames over 12 scenes) outdoor sources into the same ERP and world-to-camera pose schema, plus license-aware adapter packages for HM3D (14,475 frames over 401 rooms after local regeneration) and ScanNet++ (8,267 frames over 500 scans after local regeneration) that produce matched frames locally without redistributing licensed assets.",
-  "version": "1.0.0-anonymous",
+  "description": "CM-EVS is a curated panoramic RGB-D dataset built under a single principle: maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible. The headline release contains 11,583 ERP RGB-depth-pose frames over 326 Blender indoor scenes (CC-BY 4.0), each paired with the per-step provenance log of the depth-conflict-aware curator that selected it. The full v1.0 release additionally provides 786,344 frames re-encoded from TartanGround (783,944 frames over 63 environments) and OB3D (2,400 frames over 12 scenes) outdoor sources into the same ERP and world-to-camera pose schema, plus license-aware adapter packages for HM3D (14,475 frames over 401 rooms after local regeneration) and ScanNet++ (8,267 frames over 500 scans after local regeneration) that produce matched frames locally without redistributing licensed assets.",
+  "version": "1.0.0",
   "license": "https://creativecommons.org/licenses/by/4.0/",
   "url": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval",
   "citeAs": "@inproceedings{cmevs2026, title={{CM-EVS}: A Coverage-Curated Panoramic {RGB-D} Dataset for Indoor Scene Understanding}, author={Anonymous Author(s)}, booktitle={NeurIPS 2026 Datasets and Benchmarks Track (under review)}, year={2026}}",
@@ -57,7 +57,7 @@
     "@type": "Organization",
     "name": "Anonymous (double-blind submission)"
   },
-  "datePublished": "2026-05-07",
+  "datePublished": "2026-05-01",
   "keywords": [
     "panoramic",
     "equirectangular",
@@ -76,147 +76,107 @@
   "distribution": [
     {
       "@type": "cr:FileObject",
-      "@id": "cmevs-readme",
-      "name": "README.md",
-      "description": "Top-level dataset card: composition, output schema, license matrix, sampling methodology, and reviewer quick-sample pointer.",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/README.md",
-      "encodingFormat": "text/markdown",
-      "sha256": "f83bf6608e1a045767fd24c5cf8b9d4f4154f6e2624811b9c21848c5e2f8df6c",
-      "contentSize": "12569 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "cmevs-license",
-      "name": "LICENSE.md",
-      "description": "License matrix for every release component (Blender frames CC-BY 4.0, code MIT, adapters for upstream-gated sources).",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/LICENSE.md",
-      "encodingFormat": "text/markdown",
-      "sha256": "6c00f7c8cd699b2e706058cf03f8a12866fb588abebf80a29ba21ff4b4407ac5",
-      "contentSize": "3250 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "cmevs-changelog",
-      "name": "CHANGELOG.md",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/CHANGELOG.md",
-      "encodingFormat": "text/markdown",
-      "sha256": "335453649489fd3fa08a4296e38ba8a86dabb8455501ad9f78ef2b08a4092bd6",
-      "contentSize": "3409 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "cmevs-sha256sums",
-      "name": "SHA256SUMS",
-      "description": "Top-level integrity manifest covering 88 release artifacts (README, LICENSE, CHANGELOG, metadata, adapters, code).",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/SHA256SUMS",
-      "encodingFormat": "text/plain",
-      "sha256": "14276fb4cad7b4c9d80babd28914ac0e6c2f6e30becca11684fbe50b4305851c",
-      "contentSize": "8499 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "blender-indoor-sha256sums",
-      "name": "blender_indoor/SHA256SUMS",
-      "description": "Per-frame integrity manifest for all 39,896 Blender indoor frame files (13,631 RGB + 13,631 depth + 13,631 pose).",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/SHA256SUMS",
-      "encodingFormat": "text/plain",
-      "sha256": "0b7cf5b09cb329a5fc846a567a738b3cd682a51eebbd46ab5badb0053643bce3",
-      "contentSize": "4383575 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "frame-manifest",
-      "name": "blender_indoor/metadata/frame_manifest.csv",
-      "description": "Per-frame manifest enumerating every released ERP frame with source, scene, split, paths, pose, and curator-only provenance fields.",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/metadata/frame_manifest.csv",
-      "encodingFormat": "text/csv",
-      "sha256": "6d851b67947c8e9d2992b4fbb935db4b6cebab7ce917b0e03242d8f6e3e94c4d",
-      "contentSize": "2473669 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "splits-json",
-      "name": "blender_indoor/metadata/splits.json",
-      "description": "Default scene-level 70/15/15 train/val/test split with same-scene grouping.",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/metadata/splits.json",
-      "encodingFormat": "application/json",
-      "sha256": "072493c9e533554c0faafb1d3ba766365152f6c5084e2837d29f4d5279c76ab6",
-      "contentSize": "9537 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "source-manifest",
-      "name": "blender_indoor/metadata/source_manifest.json",
-      "description": "Per-source metadata: scene counts, frame counts, license, redistribution policy.",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/metadata/source_manifest.json",
-      "encodingFormat": "application/json",
-      "sha256": "c44fabb3932d6067704825d9af59ccf633c5129bffad9fd8a30ed4720a726ae1",
-      "contentSize": "630 B"
-    },
-    {
-      "@type": "cr:FileObject",
-      "@id": "scene-id-mapping",
-      "name": "blender_indoor/metadata/scene_id_mapping.csv",
-      "description": "Mapping from staged scene ids to upstream production scene ids (round1+2 and round2 sampling rounds).",
-      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/metadata/scene_id_mapping.csv",
-      "encodingFormat": "text/csv",
-      "sha256": "58f2ee4949e5def251babc54f39bf9ee170d482a116d0a337993726f7b565c92",
-      "contentSize": "18300 B"
+      "@id": "blender-indoor-archive.tar",
+      "name": "blender-indoor-archive.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
     },
     {
       "@type": "cr:FileSet",
       "@id": "blender-indoor-rgb",
       "name": "blender-indoor-rgb",
-      "description": "ERP panoramic RGB images, 2048x1024, one per selected viewpoint, organized as scenes/{scene_id}/panorama_{frame_idx}.png.",
       "containedIn": {
-        "@id": "cmevs-sha256sums"
+        "@id": "blender-indoor-archive.tar"
       },
       "encodingFormat": "image/png",
-      "includes": "blender_indoor/scenes/*/panorama_*.png"
+      "includes": "rgb/*.png"
     },
     {
       "@type": "cr:FileSet",
       "@id": "blender-indoor-depth",
       "name": "blender-indoor-depth",
-      "description": "ERP range depth, float32 numpy arrays in metres along ERP rays; NaN or 0 marks invalid pixels.",
       "containedIn": {
-        "@id": "cmevs-sha256sums"
+        "@id": "blender-indoor-archive.tar"
       },
       "encodingFormat": "application/octet-stream",
-      "includes": "blender_indoor/scenes/*/panorama_*_depth.npy"
+      "includes": "depth/*.npy"
     },
     {
       "@type": "cr:FileSet",
       "@id": "blender-indoor-pose",
       "name": "blender-indoor-pose",
-      "description": "Per-frame world-to-camera pose JSON: scalar-first quaternion plus position relative to the scene's first selected frame, organized as scenes/{scene_id}/pose_{frame_idx}.json.",
       "containedIn": {
-        "@id": "cmevs-sha256sums"
+        "@id": "blender-indoor-archive.tar"
       },
       "encodingFormat": "application/json",
-      "includes": "blender_indoor/scenes/*/pose_*.json"
+      "includes": "pose/*.json"
     },
     {
       "@type": "cr:FileSet",
-      "@id": "adapters-package",
-      "name": "adapters-package",
-      "description": "License-aware regeneration scripts and configs for HM3D, ScanNet++, OB3D, and TartanGround. No derived frames are redistributed; users accept upstream license terms and regenerate matched frames locally.",
+      "@id": "blender-indoor-metadata",
+      "name": "blender-indoor-metadata",
       "containedIn": {
-        "@id": "cmevs-sha256sums"
+        "@id": "blender-indoor-archive.tar"
       },
-      "encodingFormat": "application/x-python",
-      "includes": "adapters/**"
+      "encodingFormat": "application/json",
+      "includes": "metadata/*.json*"
     },
     {
-      "@type": "cr:FileSet",
-      "@id": "curator-code",
-      "name": "curator-code",
-      "description": "CM-EVS curator source code (MIT): candidate generation, geometric-validity filter, conflict-aware greedy selection, evaluation, audit.",
-      "containedIn": {
-        "@id": "cmevs-sha256sums"
-      },
-      "encodingFormat": "application/x-python",
-      "includes": "code/**"
+      "@type": "cr:FileObject",
+      "@id": "outdoor-tartanground-adapter.tar",
+      "name": "outdoor-tartanground-adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/outdoor_tartanground_adapter.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "outdoor-ob3d-adapter.tar",
+      "name": "outdoor-ob3d-adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/outdoor_ob3d_adapter.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "hm3d-adapter.tar",
+      "name": "hm3d-adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/hm3d_adapter.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "scannetpp-adapter.tar",
+      "name": "scannetpp-adapter.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/scannetpp_adapter.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "curator-source-code.tar",
+      "name": "curator-source-code.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/code.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "documentation.tar",
+      "name": "documentation.tar",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/docs.tar",
+      "encodingFormat": "application/x-tar",
+      "sha256": "TODO_SHA256"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "frame-manifest.csv",
+      "name": "frame-manifest.csv",
+      "contentUrl": "https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval/resolve/main/blender_indoor/metadata/frame_manifest.csv",
+      "encodingFormat": "text/csv",
+      "sha256": "c1bfd6220ae0b8155e281c3cb23b78e009437dd0ee208721e216b0a12d31556f"
     }
   ],
   "recordSet": [
@@ -233,7 +193,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "frame_id"
@@ -247,7 +207,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "source"
@@ -261,7 +221,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "scene_id"
@@ -275,7 +235,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "room_id"
@@ -289,7 +249,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "split"
@@ -303,7 +263,7 @@
           "dataType": "sc:ImageObject",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "rgb_path"
@@ -317,7 +277,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "depth_path"
@@ -331,7 +291,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "pose_quaternion"
@@ -345,7 +305,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "pose_position"
@@ -359,7 +319,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "camera_type"
@@ -373,7 +333,7 @@
           "dataType": "sc:Float",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "viewpoint_score"
@@ -387,7 +347,7 @@
           "dataType": "sc:Float",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "coverage_gain"
@@ -401,7 +361,7 @@
           "dataType": "sc:Float",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "conflict_ratio"
@@ -415,7 +375,7 @@
           "dataType": "sc:Text",
           "source": {
             "fileObject": {
-              "@id": "frame-manifest"
+              "@id": "frame-manifest.csv"
             },
             "extract": {
               "column": "candidate_id"
@@ -451,4 +411,4 @@
     "Synthetic Blender materials may not match real-scan sensor noise."
   ],
   "rai:dataSocialImpact": "CM-EVS lowers the engineering cost of producing auditable panoramic RGB-D resources from existing 3D scenes. Positive uses include panoramic perception, data-centric evaluation, view-planning research, and 3D-consistent world-model pretraining. Potential harms include over-trusting synthetic data, obscuring upstream dataset bias, and using real indoor scans in privacy-sensitive settings. The release therefore separates public synthetic frames from licensed real-scan regeneration and documents intended uses, non-uses, and source licenses."
-}
+}