depth
Datasets
All datasets matching “depth”VLADBenchmdm_depth
LingBot-Depth Dataset
Self-curated RGB-D dataset for training LingBot-Depth, a masked depth modeling approach (arxiv:2601.17895). Each sample contains an RGB image, raw sensor depth, and ground truth depth.
Total size: 2.71 TBDepth scale: millimeters (mm), stored as 16-bit PNGLicense: CC BY-NC-SA 4.0
Sub-datasets
Name
Description
Samples
RobbyReal
Real-world indoor scenes captured with multiple RGB-D cameras
1,400,000
RobbyVla
Real-world data… See the full description on the dataset page: https://huggingface.co/datasets/robbyant/mdm_depth.BEDLAM-depth
Dataset Mirror of BEDLAM Dataset (Depth Data Subset)
Project site: https://bedlam.is.tuebingen.mpg.de/
Please register at project site for additional information and data (Download section)
Related Hugging Face dataset mirror: BEDLAM
Dataset Information
Depth maps (EXR, 32-bit, 3.8TB)
Camera ground truth information is not included but can be found in the BEDLAM dataset mirror
Image/video data with motion blur is not included but can be found in the BEDLAM dataset… See the full description on the dataset page: https://huggingface.co/datasets/Intelligent-Systems/BEDLAM-depth.RoboTwin2.0-DepthBEDLAM2-depth
Dataset Mirror of BEDLAM2.0 Dataset (Depth Data Subset)
Project site: https://bedlam2.is.tuebingen.mpg.de/
Please register at project site for additional information and data in its Download section.
Related Hugging Face dataset mirror: BEDLAM2
Dataset Information
Depth maps (Multilayer EXR, 16-bit, available for 44% of images, 15TB)
Multilayer EXR details
16-bit float depth in red channel (FinalImageMovieRenderQueue_WorldDepth.R)
Color image without motion blur
Body… See the full description on the dataset page: https://huggingface.co/datasets/Intelligent-Systems/BEDLAM2-depth.Bench2Drive-V0.0.4-depth
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving.
New Features
This is the new 0.0.4 version of Bench2Drive dataset with strictly uniform training data: The new Think2Drive-collected training set (44 scenarios × 25 routes = 1,100 routes) is strictly uniform over scenarios, unlike the previous Base set whose scenario distribution is uneven.
Also introduced new modality: 3D occupancy (3D occ).
This repo only includes the… See the full description on the dataset page: https://huggingface.co/datasets/Bench2DriveData/Bench2Drive-V0.0.4-depth.