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Lightwheel

EgoStandard

The 90,000-hour head-view line of EgoSuite-Open100K.

Data Bucket · Collection · EgoDemo · EgoPro · Project page

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Data location: EgoStandard is distributed through the LightwheelAI/EgoStandard Bucket. This Git repository is the dataset card and access point; download the data from the Bucket.

Overview

EgoStandard pairs head-view egocentric video with synchronized 3D hand pose. Its body subset adds full-body pose. Wrist-view video is not part of either EgoStandard Sub-SKU. LeRobot and MCAP are alternative representations of the same episodes and must not be counted as additional hours.

Sub-SKU Planned duration Camera views Pose annotations
EgoStand 80,000 hours Head Hands
EgoStand-body 10,000 hours Head Hands, full body

Temporal event-level semantic annotations are included as a complimentary release add-on.

Data Access

After access is approved, install and authenticate the Hugging Face CLI:

pip install -U huggingface_hub
hf auth login

Inspect the available prefixes before downloading:

hf buckets list LightwheelAI/EgoStandard -h -R

Download a selected directory or a single file:

# Replace PREFIX and LOCAL_DIR with paths chosen from the listing
hf buckets sync hf://buckets/LightwheelAI/EgoStandard/PREFIX ./LOCAL_DIR

# Replace PATH/TO/FILE and FILE with the selected object path and filename
hf buckets cp hf://buckets/LightwheelAI/EgoStandard/PATH/TO/FILE ./FILE

The Bucket is large and mutable, so its current file listing and manifests are the source of truth for published prefixes. See the Hugging Face Bucket guide for filtering, mounting, Python access, and sync options.

Privacy and Use

Recordings were processed through an automated de-identification pipeline with human verification, including blurring of faces, license plates, and other personally identifiable information. All participants provided informed consent covering collection, annotation, controlled release, and uses permitted by the dataset license. Use of the data is governed by the repository license and access terms.

For dataset questions, open a discussion in this repository. For other inquiries, contact [email protected].

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