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. The Blender indoor frames are the only redistributable RGB-D data. For the four restricted sources, this dataset ships the per-source adapter (config + pipeline script + scene-id metadata); users obtain upstream data themselves and run the adapter locally to reproduce matching ERP frames under the unified…
SAVRN Model Hub · Datasets by Task
Depth Estimation Datasets
3 open-weight depth estimation datasets in the SAVRN Model Hub, with Origin Lab, Arc and Lyu Rui publishing the most.
3Datasets
3Publishers
2Licenses
Most Downloaded
| Dataset | Publisher | License | Monthly downloads |
|---|---|---|---|
| cmevs-erp-eval | Arc | other | 45.7k |
| game-recordings-v4 | Origin Lab | other | 14 |
| DrivingStereo | Lyu Rui | mit | — |
Licenses
| License | Datasets | Commercial use |
|---|---|---|
| other | 2 | Read the license |
| mit | 1 | Yes |
Who Publishes Them
| Publisher | Datasets |
|---|---|
| Origin Lab | 1 |
| Arc | 1 |
| Lyu Rui | 1 |
All 3 Datasets
Human gameplay captured in-engine under per-title licenses at 1080p / 60 FPS CFR on one shared frame clock: every stream starts at frame 0 and frame k matches frame k across pre-HUD and post-HUD RGB, surface normals, metric depth, audio, camera telemetry, keyboard and mouse inputs, in-engine action events and game state, and world telemetry, plus per-frame training tables. This release nearly doubles the roster to 19 games with balanced per-game hours, and adds the first Unity-engine title alongside Unreal. Watch full playable previews of every modality, side by side and in sync, at app.originlab.ai/data. Four games, side by side. Each tile is one session's mosaic: its four visual streams…
This is a mirror of the original DrivingStereo download files, preserving the original ZIP archives and camera calibration text files without recompression. The original dataset was introduced at CVPR 2019 by Guorun Yang, Xiao Song, Chaoqing Huang, Zhidong Deng, Jianping Shi, and Bolei Zhou. The inventory contains 300 source files totaling 202,346,258,264 bytes (202.346 GB). The early demonstration package is excluded; the released training, testing, weather, and calibration directories are mirrored in full. Transfer in progress. As of 2026-10-17T03:37:54+00:00, 0/300 files (0.000/202.346 GB) are verified on the Hub. Status is refreshed after each batch. transferstatus.json contains the…