---
license: other
task_categories:
- robotics
tags:
- hand-pose
- mano
- egocentric
- vitra
- gigahands
- quality-audit
size_categories:
- 1M<n<10M
pretty_name: GigaHands VITRA official-MANO strict-v1
---

# GigaHands → VITRA official-MANO strict-v1

VITRA Stage-1 annotations derived from GigaHands' official MANO fit, regenerated with strict
video/annotation binding and accompanied by an exhaustive numerical audit plus an every-episode RGB
audit. This repository contains **annotations only**: it does not redistribute GigaHands videos or
the licensed MANO model.

| item | value |
|---|---:|
| source manifest entries | 13,249 |
| converted episodes | **12,783** |
| train / test episodes | 11,461 / 1,322 |
| converted frames | **3,227,699** |
| train / test frames | 2,963,261 / 264,438 |
| camera | `brics-odroid-001_cam0` |
| action interface | VITRA `keypoints` mode (`16 × 192` future action chunks at training time) |

Although the source is the official MANO fit, this is not a MANO-angle-only target dataset. Each
episode contains MANO-derived 3-D joints, wrist transforms, MANO shape, global orientation, and
finger rotation matrices. Current VITRA training uses the 3-D joint/keypoint action interface.

## What changed from `yuzhench/gigahands-vitra-mano`

The older release retained 453 known video-length mismatch candidates. Strict-v1 applies the
following deterministic gates before writing an episode:

1. bind `(scene, sequence, camera)` to the exact video in GigaHands'
   `multiview_camera_video_map.csv`, never to a sorted file-list position;
2. require exact temporal agreement among left/right MANO parameters and
   `keypoints_3d_mano`;
3. reject video/annotation length differences above 12 frames and trim only a short video tail
   within that tolerance;
4. require at least 0.9 raw-triangulation validity using `chosen_frames_{left,right}.json`, rather
   than treating the always-finite MANO-filled output as 100% valid.

Conversion removed 464 entries: 381 for video/annotation length disagreement and 83 for missing
official video mapping. One entry lacked MANO keypoints and one was shorter than 32 frames. None of
the older release's 453 known length-misaligned episode IDs remains in strict-v1.

Reproduction code is in
[`kaichen-z/VLA-HAND@4458502`](https://github.com/kaichen-z/VLA-HAND/tree/4458502), including:

- `scripts/build_gigahands_official_mano_strict_v1.sh`
- `scripts/run_gigahands_full_quality_audit.sh`
- `data/preprocessing/convert_gigahands_to_vitra_stage1.py`
- `tools/audit_gigahands_full.py`

## Contents

```text
Annotation/
├── gigahands_real_train/
│   ├── episodic_annotations.tar.zst       # 11,461 .npy episodes
│   ├── episode_frame_index.npz            # 2,963,261 frame/window-start entries
│   └── conversion_report.json
├── gigahands_real_test/
│   ├── episodic_annotations.tar.zst       # 1,322 .npy episodes
│   ├── episode_frame_index.npz            # 264,438 entries
│   └── conversion_report.json
└── statistics/
    ├── gigahands_real_train_keypoints_statistics.json
    └── gigahands_real_test_keypoints_statistics.json
subset_manifest.json                        # original 13,249-entry source manifest
conversion_report.json
quality_rejections.json
quality_comparison.{json,md}
baseline_residual_misaligned_episodes.json
artifact_manifest.json                       # byte size and SHA-256 for every uploaded artifact
quality/full_quality_audit/
├── full_audit_report.{json,md}
├── recommended_exclude_episode_ids.json
├── audit_categories.json
├── labels_summary.json
├── labels_per_episode.jsonl
├── video_summary.json
├── video_per_episode.jsonl
├── video_samples.jsonl
├── rgb_alignment_manual_review.json
└── *_review_*.jpg
```

The `.tar.zst` files contain an `episodic_annotations/` directory. Extract them in place:

```bash
huggingface-cli download \
  --repo-type dataset \
  LeoJiangOR/gigahands-vitra-mano-strict-v1 \
  --local-dir datasets/vitra_gigahands_official_mano_strict_v1

for split in train test; do
  tar --zstd -xf \
    datasets/vitra_gigahands_official_mano_strict_v1/Annotation/gigahands_real_${split}/episodic_annotations.tar.zst \
    -C datasets/vitra_gigahands_official_mano_strict_v1/Annotation/gigahands_real_${split}
done

mkdir -p datasets/vitra_gigahands_official_mano_strict_v1/Video
ln -s /path/to/GigaHands/multiview_rgb_vids \
  datasets/vitra_gigahands_official_mano_strict_v1/Video/GigaHands_root
```

## Episode schema

Each `.npy` loads as a Python dictionary. `left` and `right` contain:

| field | shape | meaning |
|---|---:|---|
| `beta` | `(10,)` | official MANO shape |
| `global_orient_worldspace` | `(T,3,3)` | wrist/global orientation in the GigaHands world frame |
| `global_orient_camspace` | `(T,3,3)` | orientation in the selected camera frame |
| `hand_pose` | `(T,15,3,3)` | MANO finger rotations with the MANO mean pose restored |
| `transl_worldspace` | `(T,3)` | wrist position, equal to `joints_worldspace[:,0]` |
| `transl_camspace` | `(T,3)` | wrist position in camera coordinates |
| `joints_worldspace` | `(T,21,3)` | official-MANO joints with global translation restored |
| `joints_camspace` | `(T,21,3)` | joints in camera coordinates |
| `kept_frames` | `(T,)` | validity mask |

Episodes also contain `video_name`, `video_decode_frame`, language instruction, intrinsics,
extrinsics, and camera metadata. Sixteen-frame action windows are created by the VITRA loader; each
stored `.npy` is a complete episode rather than one training window.

## Full quality audit

Coverage:

- 12,783 / 12,783 episodes;
- 3,227,699 / 3,227,699 label frames for schema, finite values, rotations, world/camera transforms,
  temporal continuity, distortion-aware camera projection, and comparison with independent raw
  triangulated keypoints;
- 63,915 / 63,915 RGB checks: five evenly spaced frames in every episode, using a hand-pose detector
  and manual review of every automatic mismatch candidate.

Main results:

| category | episodes | rate |
|---|---:|---:|
| structural fatal error | 0 | 0.000% |
| likely left/right identity swap | 0 | 0.000% |
| neither hand visible in cam0 for more than half the episode | 1,353 | 10.584% |
| neither hand visible in cam0 for the entire episode | 399 | 3.121% |
| persistent MANO/triangulation disagreement above 5 cm median | 6 | 0.047% |
| converted-output wrist jump above 25 cm/frame | 2 | 0.016% |
| automatic RGB alignment suspects | 18 | 0.141% |
| manually confirmed RGB mismatch among those suspects | 0 | 0.000% |

The typical per-episode MANO-versus-independent-triangulation median MPJPE is approximately 7 mm.
Of 213 tail-disagreement candidates, 185 are more consistent with a discontinuous triangulation
reference; the remaining 28 are retained in the conservative exclusion/review category.

`quality/full_quality_audit/recommended_exclude_episode_ids.json` contains a conservative
episode-level training policy: 1,384 episodes (10.827%). Applying it leaves 11,399 episodes and
2,863,827 frames (train: 10,296 episodes / 2,637,406 frames; test: 1,103 episodes / 226,421 frames).
Most exclusions are **not proven source corruption**: they are cam0 visibility failures. If another
official camera is available, selecting the camera with the best projected-hand visibility is better
than discarding the underlying multiview motion. If training must remain cam0-only, use this list or,
preferably, filter individual 16-frame windows by hand visibility.

The 18 automatic RGB suspects were all manually cleared. Typical detector failures were firing on a
monitor, an object, or a toy dog while the projected MANO joints still followed the real, partially
cropped hand. Review images and the decisions are included instead of silently converting detector
output into deletion labels.

## Video mapping

Videos are not included. Obtain them under the original GigaHands terms and place or link
`multiview_rgb_vids` at `Video/GigaHands_root`. `video_name` in every episode and
`video_path`/`start_frame`/`end_frame` in `subset_manifest.json` give the exact source mapping.

Do not infer a sequence's video by list index: sequence IDs contain gaps. Strict-v1 verifies the
official CSV mapping during conversion.

## Licence and citation

These are derived GigaHands annotations. The original images, videos, MANO fits, and their usage
terms remain with the GigaHands authors. Follow the original GigaHands licence and citation
requirements. The MANO model is not redistributed and must be obtained separately under its own
licence. The annotation format follows Microsoft VITRA Stage-1.