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---
license: other
license_name: fair-noncommercial-research-license-v1
license_link: https://huggingface.co/datasets/Rice-RobotPI-Lab/egoinfinity/blob/main/LICENSE-Action100M
pretty_name: EgoInfinity
tags:
- egocentric
- hand-tracking
- 3d-scene
- video
- action-recognition
- derivative-of-action100m
---
# EgoInfinity Dataset
Derivative scene assets for a curated subset of [Action100M] (Meta FAIR)
clips. Used as the data backend for the
[EgoInfinity Browser](https://huggingface.co/spaces/Rice-RobotPI-Lab/egoinfinity)
Space.
[Action100M]: https://github.com/facebookresearch/Action100M
## Contents
```
samples/
├── index.json # browse-time episode list (consumed by the Space)
└── <clip_id>/
├── scene.json # camera intrinsics, object metadata, durations
├── signals.json # per-frame action signals (timeseries)
├── thumb.jpg # 320×180 preview rendered from depth
├── depth.mp4 # MoGe-2 depth, inferno colormap (854×480)
├── flow.mp4 # MEMFOF optical flow visualization
├── mask.mp4 # SAM-tracked object mask cutout
├── recording.viser # full 3D scene (point cloud + meshes + hands)
├── hand_joints.bin # (T, H, 21, 3) float32 — 3D joint positions
├── hand_verts.bin # (T, H, 778, 3) float32 — baked MANO vertices
├── hand_faces.bin # (F, 3) uint16 — MANO topology
└── hand_meta.json # bone connectivity + helper metadata
```
`<clip_id>` is `<youtube_video_id>_<start_sec>_<end_sec>`. The only original
YouTube pixels that appear in this repository are inside the SAM-tracked
object region of `mask.mp4` (everything outside the mask is painted black);
no full source frames are redistributed.
## License
This dataset is released under the FAIR Noncommercial Research License v1
(see [LICENSE-Action100M](LICENSE-Action100M)) for **noncommercial research
use only**. Per Section 1.b.ii, redistribution must include a copy of this
license file.
### Attribution
- **Source clips** are from [Action100M] (Meta FAIR). Full source videos
remain on YouTube; only the SAM-tracked region appears in `mask.mp4` as
a per-frame cutout.
- **Depth maps** were generated using MoGe-2.
- **Optical flow** was computed using MEMFOF.
- **Object segmentation** uses Meta SAM-3 / SAM-3D.
- **Hand parameters** were estimated using a WiLoR-based pipeline. Vertex
positions are baked from the MANO model (Romero et al., 2017); MANO weights
are not redistributed.
## Citation
```bibtex
@misc{egoinfinity2026,
title = {EgoInfinity: TBD},
author = {Rice Robot Perception \& Intelligence Lab},
year = {2026},
note = {Preview release}
}
```