README.md

metadata

license: other
license_name: worldrover-research
pretty_name: WorldRover 6-scene paired panoramic + first-person
task_categories:
  - depth-estimation
  - robotics
tags:
  - video
  - panoramic
  - equirectangular
  - depth
  - camera-pose
  - embodied-ai
  - world-model
  - synthetic
size_categories:
  - n>1T

WorldRover-6scenes

600 camera paths through six photoreal 3D environments, each rendered twice — once as a 360° panorama, once as a first-person pinhole view — with per-frame metric depth, camera pose and action labels. 1200 clips, 18.9 h of video per view (37.9 h total) at 30 fps, 2.05 M frames per view, ~7.6 TB.

Scene	Clips per view	Median clip	Range	Video per view
med_village	100	2 min 17 s	30 s – 6 min 40 s	4.54 h
venice	100	1 min 42 s	21 s – 8 min 32 s	4.19 h
apartment	100	1 min 39 s	29 s – 3 min 00 s	2.91 h
paris	100	1 min 39 s	37 s – 3 min 00 s	2.86 h
office	100	1 min 15 s	16 s – 3 min 01 s	2.25 h
art_nouveau	100	1 min 01 s	11 s – 4 min 07 s	2.19 h

Layout

<scene>/pano/<clip_id>/     equirectangular 4096x2048
<scene>/fp/<clip_id>/       pinhole 1280x720, hfov 65.5 deg (28 mm on a 36 mm sensor)
    rgb.mp4                 H.264, 30 fps
    depth/depth.mkv         FFV1 gray16le, lossless, log-quantized radial depth
    depth/depth.meta.json   near/far, frame count, decode formula
    camera_trajectory.csv   per-frame world pose + intrinsics
    description.json        scene, asset pack, licence, trajectory summary, render settings
    gamepad_format/         action labels (axis events + timeline)
    trajectory.png          top-down path plot (fp only)

Paired, frame for frame

pano/<clip_id> and fp/<clip_id> are the same camera path: the first-person clip is rendered from the panoramic clip's per-frame trajectory, so the two camera_trajectory.csv files agree row for row (only hfov_deg/focal_length_mm differ — 360°/0 mm for the equirect camera, 65.47°/28 mm for the pinhole). You get the same world state under two very different projections without an interpolated alignment.

Clips are 11 s to 8.5 min of continuous motion — no cuts, no teleports.

Conventions that are easy to get wrong

• Depth is log-quantized and radial. depth_m = exp(gray/65535 * (log 200 − log 0.1) + log 0.1), and the value is distance along the ray, not along the optical axis — convert before unprojecting.
• Frame counts. camera_trajectory.csv has one row more than the video has frames (the last row is the closing keyframe). The authoritative count is depth/depth.meta.json.
• Poses are Unreal-style: left-handed, centimetres, X-forward / Y-right / Z-up, camera looking down its own +X.
• Panoramic frames are equirectangular. A rectangular crop is not a perspective view — reproject before comparing against the first-person clip.

Render provenance

description.json records the exact render path per clip, and it is not identical across scenes. Five scenes (med_village, venice, office, apartment, art_nouveau) were rendered in two rounds — MPPC_RGBOnly then MPPC_DepthPlus — and stitched with a Lanczos kernel, so render.mppc is an object with rgb/depth keys. paris was re-rendered later through a corrected single-pass path (MPPC_VelocityDepthPlus with the extra pass dropped, linear-HDR output, fixed exposure, linear stitch kernel), so its render.mppc is a plain string and its render.cube additionally carries fixed_ev and tm_comp.

The reason for the paris re-render: a Lanczos resampling kernel has negative lobes, which on high-contrast sky/architecture boundaries interpolate linear HDR below zero; clamping to zero left a one-pixel pure-black rim along building silhouettes. Switching to a linear kernel took sky edges with undershoot from 15.5% to 3.4% — below the 6.1% baseline of the cube faces themselves. Per-frame auto-exposure was replaced with a fixed value at the same time, so brightness no longer drifts with what happens to be in view.

Tools

git clone https://github.com/AlayaLab/WorldRover
pip install -r WorldRover/tools/requirements.txt   # numpy, opencv-python; ffmpeg/ffprobe on PATH
cd WorldRover/tools                                # the package is not pip-installable yet

from worldrover import Clip

clip    = Clip("/data/WorldRover-6scenes/venice/fp/venice_000000")
rgb     = clip.rgb_frame(100)     # uint8 (H, W, 3), sRGB
depth_m = clip.depth_frame(100)   # planar depth in metres
pts     = clip.points_world(100)  # world points, centimetres
poses   = clip.poses              # per-frame pose + intrinsics

Clip takes a filesystem path to a clip directory. The reader takes the depth pixel format from that clip's own depth/depth.meta.json, so it handles both encodings used across these repositories, and it converts radial depth and the off-by-one trajectory row for you.

Related

• WorldRover-preview — the original release as a lite subset (no depth)
• Collection — every part in one place
• WorldRover-styles — the same kind of trajectories re-rendered under six lighting/style treatments

License

Rendered video, depth, camera pose and action labels are released for research use. The underlying 3D environments are third-party commercial assets, are not redistributed here, and each clip's description.json records its asset pack and licence. Tools are MIT.