Buckets:
| Name | Size | Uploaded | Xet hash |
|---|---|---|---|
| IRIS+226b9f35+2023-07-11-12h-01m-54s.mp4 | 35.9 MB xet | 8c1709fd | |
| RAD+62828209+2023-09-09-09h-01m-13s.mp4 | 42 MB xet | 0cf89086 | |
| RAIL+80edfcb1+2023-04-26-15h-45m-39s.mp4 | 18.7 MB xet | bc826226 | |
| RAIL+80edfcb1+2023-06-29-12h-44m-09s.mp4 | 38.8 MB xet | 49a2d707 | |
| README.md | 3.57 kB xet | 37085305 | |
| summary.json | 4.33 kB xet | c9c809cc |
MoGe-2 monocular depth — qualitative previews
Full-length monocular depth over the clips published in this bucket, rendered as a 2x2 panel video (2560x1440, 15 fps): RGB | depth (global range) | the same depth at a near-field range | normal, each panel at the clip's native 1280x720.
These are previews for judging detail by eye. They are not a dataset tier and
nothing in the pipeline consumes them — the pipeline's own depth comes from
PointWorld scene_flows (sparse metric 3D tracks), not from MoGe.
Model
Ruicheng/moge-2-vitl-normal, resolution_level=9.
resolution_level=9 is the default and already maps to the top of MoGe-2's
num_tokens_range (3600 tokens) — the finest setting the model offers.
MoGe-3 is not used, because it does not exist as runnable code. The paper
(arXiv 2607.17967, "Fine-Detail Monocular Geometry Estimation…") was announced in
the upstream README on 2026-07-21, but at pinned commit 925b8ed — still
origin/main as of this run — there is no moge/model/v3.py and the pretrained
table lists moge-3-vitg/moge-3-vitl as "coming soon" with no HF repo id.
How to read the panels
- Depth uses one global normalisation for the whole clip (robust 2/98 percentiles over every valid pixel of every frame), never per frame. Per-frame normalisation makes the panel breathe as the near/far extremes move, which by eye is indistinguishable from the model's own temporal instability — the exact thing these videos exist to let someone judge. The colour range in metres is burned into the panel label.
- Normal is where fine detail actually shows. Depth is dominated by the metre-scale front-to-back ramp of the workbench; the normal map spends its whole colour budget on surface relief instead.
- No
fov_xwas passed, so MoGe estimates its own FOV per frame even though this project knows the true DROID intrinsics. That is the out-of-the-box path — priming the model with the calibration would measure a best case that arbitrary video would not get. - Videos are muxed at 15 fps, the DROID trajectory rate. The source mp4
containers advertise 60/1, but their frames are the 15 Hz trajectory samples (this
repo indexes poses per video frame at
DEFAULT_TRAJECTORY_FPS = 15.0). Playing at 60 would look like temporal jitter that is not there.
Clips
| file | camera / class | frames | depth range (m) | near mm/level | size |
|---|---|---|---|---|---|
IRIS+226b9f35+2023-07-11-12h-01m-54s.mp4 |
IRIS / rigid_symmetric | 358 | 0.23–1.24 | 0.8 | 35.9 MB |
RAD+62828209+2023-09-09-09h-01m-13s.mp4 |
RAD / rigid_thin | 602 | 0.53–4.22 | 1.1 | 42.0 MB |
RAIL+80edfcb1+2023-04-26-15h-45m-39s.mp4 |
RAIL / deformable | 191 | 0.32–3.07 | 2.2 | 18.7 MB |
RAIL+80edfcb1+2023-06-29-12h-44m-09s.mp4 |
RAIL / articulated | 428 | 0.30–5.05 | 1.6 | 38.8 MB |
The near mm/level column is the one to read before trusting a panel: it is the millimetres of depth per colour level in the near-field panel. Scenes with a deep background push the global panel to 15–19 mm/level, where nothing object-sized is visible at all; the near-field panel is what stays readable.
These clips come from the diversity sample: different labs, different object classes, different scene depths. That is what makes them worth looking at — and also why the per-clip colour ranges differ so much. Do not compare colours between two clips; only the near-field range printed in each panel makes a panel's colours mean anything.
- Total size
- 792 MB
- Files
- 130
- Last updated
- Aug 5
- Pre-warmed CDN
- US EU US EU