adapters/README.md

Adapter packages — license-aware regeneration for restricted sources

The four sources here (HM3D, ScanNet++, OB3D, TartanGround) cannot be redistributed as ERP RGB-D frames under their upstream licenses. Instead, each adapter package contains:

1. A config.yaml with all curator / re-encoding parameters used in the paper (resolution, grid spacing, fixed-budget K, thresholds, …).
2. A pipeline.py (curator adapters) or reencoding_script.md (outdoor re-encoders) describing exactly which command to run and which input layout it expects.
3. A metadata/source_manifest.json listing the upstream scene / scan / part IDs that the paper's K=30 evaluation runs over.

Users that want to reproduce the per-source ERP frames acquire the upstream data themselves (after accepting upstream license terms) and run the adapter locally.

Per-source quick reference

Source	License gate	Adapter type	Scene count
HM3D	Matterport / HM3D EULA	curator (NavMesh-based room proposal → CM-EVS greedy)	401 rooms
ScanNet++	ScanNet++ ToS	curator (mesh / point-cloud modes)	500 scans
OB3D	per upstream	re-encoding (cubemap → ERP, pose unification)	24 instances (12 scenes × 2 viewpoints)
TartanGround	per upstream (typically CC-BY-NC-SA)	re-encoding (cubemap → ERP, pose unification)	762 parts (~11 environments)

Curator adapters (HM3D, ScanNet++)

These plug into the standard CM-EVS pipeline:

scene asset → adapter (load + normalize + propose candidates) → curator greedy selection →
high-res Cycles ERP render → unified output schema

The adapter handles three things specific to that source:

• Asset loading (HM3D: .glb; ScanNet++: .ply point cloud or mesh).
• Candidate proposal (HM3D: NavMesh / cluster / label-based; ScanNet++: mesh / point-cloud sampling).
• Source-specific failure modes (e.g. ScanNet++ point-cloud mode degrades surface tests to AABB + splat Z-buffer).

To run an adapter:

cd ../code
python pipelines/run_hm3d_pipeline.py     --config ../adapters/hm3d/config.yaml
# or
python pipelines/run_ply_pipeline.py      --config ../adapters/scannetpp/config.yaml

Both adapters write to outputs/<source>/<scene_id>/{rgb,depth,pose,metadata}/... under the same schema as blender_indoor/scenes/.

Re-encoding adapters (OB3D, TartanGround)

These do not run the curator. Their job is to take dense RGB-D-pose trajectories already shipped by the upstream source and re-express them in CM-EVS's unified ERP + world-to-camera pose convention:

• Cubemap → ERP at the source's native resolution.
• Pose re-expressed in right-handed +Y-up world frame with scalar-first q_wc.
• The full re-encoded trajectory is released — outdoor frames are not curator-selected subsets and therefore do not carry per-step provenance logs (per_step_log.jsonl).

The reencoding_script.md inside each package documents the exact command, expected upstream layout, and output schema.

Source-id metadata

metadata/source_manifest.json in each adapter package lists the upstream IDs that the paper's reported numbers are computed over. If you need to reproduce the exact numbers in §5.4 (cross-source) or §4.10 (downstream), use only these IDs.

Caveat: depending on each upstream license, simply listing scene IDs may itself be restricted. Before redistributing or quoting these manifests verbatim, check the upstream's terms. See ../LICENSE.md.

Anonymous review note

For NeurIPS double-blind review, no upstream credentials are required to inspect this directory: the adapters list IDs and parameters, but no upstream data ships here. To execute an adapter, the reviewer must independently obtain the upstream dataset.