SlugTrails 1.0

SlugTrails is an egocentric floor-plan localization benchmark for large indoor buildings.
This Hugging Face package (slugtrails-1.0) is the canonical public data blob: anonymized RGB, Project Aria MPS trajectories, floor-plan–aligned ground truth, CAD-derived maps, and official evaluation / finetune splits.

Release id	slugtrails-1.0 (package 1.0.0)
License	CC BY 4.0
Code & tools	github.com/Head-inthe-Cloud/SlugTrails
Paper	Cheng & Manduchi — SlugTrails: An Egocentric Benchmark for Floor Plan Localization in Large Buildings (2026)

manifests/ holds our official splits for the paper protocol (SHA-256 digests in RELEASE.json). You may define your own sampling if you prefer; numbers comparable to the paper should use these manifests.

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What’s inside

• 3 campus buildings / 6 floors — floor-plan outline 22 089 m², circulation space 5317 m² (same figures as the paper)
• 6 Aria sessions (~30 Hz RGB); trajectory length ≈ 1.80 km (≈ 1.57 km excluding panorama spins)
• CAD floor plans with semantic classes + outline + circulation masks (meters)
• MPS open-loop and closed-loop device trajectories (Meta export) + semidense point clouds (mps/slam/semidense_points.csv.gz) for Aria Studio / Rerun viewing
• Factor-graph GT (gt_aligned/) in the same meter frame as the maps
• Official protocols: single-frame, multi-view sweep, walking sequence + finetune session split

Not in 1.0: raw VRS, SLAM-camera videos, MoGe depths, extra non-protocol sessions.

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Quick layout

slugtrails-1.0/
├── README.md                 ← this card
├── RELEASE.json
├── CHECKSUMS.sha256
├── maps/<floor_stem>/        ← walls, doors, windows, … outline, circulation
├── manifests/                ← official eval / finetune splits
└── recordings/<recording_id>/
    ├── RECORDING.json
    ├── rgb/                  ← anonymized camera-rgb_undistorted.mp4 + timestamps
    ├── mps/{closed,open,slam}/  ← traj + semidense_points.csv.gz
    ├── gt_aligned/           ← canonical SE(3) GT @ ~30 Hz (eval lookup)
    ├── labels/
    ├── alignment/            ← coarse SE(2) prior to FG
    └── metadata/             ← sanitized Aria metadata + RGB intrinsics

Per-folder docs: maps/README.md · manifests/README.md · recordings/README.md.

Protocol recordings

Recording	Floor map
BE_0_0	maps/BE_0/
BE_1_0	maps/BE_1/
BE_2_0	maps/BE_2/
E2_2_0	maps/E2_2/
E2_3_0	maps/E2_3/
PS_2_0	maps/PS_2/

Leave-out roles (finetune / paper): ID test session BE_2_0, OOD test session PS_2_0 — see manifests/finetune_session_split.json.

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Coordinate frames (read this once)

Asset	Frame
maps/*	Floor-plan meters; origin = CAD footprint bottom-left (after unit scale). Not geographic north unless the DXF already was.
gt_aligned/	Same map frame (factor-graph alignment of MPS closed-loop → plan).
mps/closed, mps/open	Meta MPS device poses (meters) in the MPS frame — not the floor-plan frame.
Timestamps	Aria device nanoseconds across RGB, MPS, labels, GT.

Eval scoring looks up nearest gt_aligned/ pose by timestamp_ns.

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Official evaluation protocols

Manifest	Task	Size (this release)
direct_single_manifest.json	One walking RGB → SE(2)	1296 samples @ 1 Hz (pano / pitch filters)
direct_sweep_manifest.json	Stationary multi-view spin → one pose	2880 sweeps (180°/270°/360° tiers)
sequential_stream_manifest.json	Walking stream + relative motion	600 sequences / 26400 frame rows @ 2 Hz, seed 42
finetune_session_split.json	Train / ID / OOD session carve	roles into the three tasks

SHA-256 digests for these files are listed in RELEASE.json (also covered by CHECKSUMS.sha256).

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Privacy / anonymization

Public RGB was anonymized before release. Faces / heads were detected with SAM3, then manually inspected and blurred (elliptical Gaussian blur baked into rgb/camera-rgb_undistorted.mp4).

We also checked individual name tags: none appear as readable text under our QA, so no further redaction was needed for names. Room numbers remain visible (building wayfinding; not personal PII).

Although we have done our best to anonymize, if you need additional anonymization, contact the corresponding author at ychen827@ucsc.edu.

Capture is in public / circulation spaces of campus buildings.

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Verify download

From a checkout of the code tools (public GitHub) with this tree as the data root:

# Example: confirm RELEASE.json + manifest digests (API may take a data root flag —
# see the public repo README for the exact verify_release invocation once published.)
sha256sum -c CHECKSUMS.sha256 | tail

Spot-check one recording: open recordings/BE_2_0/rgb/camera-rgb_undistorted.mp4, load gt_aligned/trajectory_positions.npy, confirm RECORDING.json → anonymization.status == "done".

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Citation

If you use SlugTrails, please cite the paper: https://arxiv.org/abs/2609.19876

@inproceedings{Cheng2026SlugTrailsAE,
  title={SlugTrails: An Egocentric Benchmark for Floor Plan Localization in Large Buildings},
  author={Yunqian Cheng and Roberto Manduchi},
  year={2026}
}

Also cite Project Aria / MPS and any baseline methods you evaluate under their own licenses.

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Contact

Yunqian Cheng (ychen827@ucsc.edu) · Roberto Manduchi (manduchi@ucsc.edu)
UC Santa Cruz — Computer Science and Engineering

Issues / data questions: GitHub Issues on the public repo.