---
license: apache-2.0
task_categories:
  - translation
  - video-classification
language:
  - vi
configs:
  - config_name: default
    data_files:
      - split: train
        path: "data/shard_*-train.parquet"
---
# TriViS-MediaPipe

MediaPipe Holistic 3D keypoints extracted from **TriViS**, a continuous Vietnamese Sign Language video dataset (~84.5k videos, 12,000 sentences, 3 synchronized camera views).

## Dataset overview

- **Views**: every take is recorded by 3 cameras (`front`, `left`, `right`). `group4` file names say `center` for the front camera; the `view` field always uses the CSV value.
- **Scenes** (metadata field `scene`):
  - `lab`: 72,453 clips (24,151 takes × 3 views) of 12,000 sentences recorded in a studio, all 4 signer groups. Includes 108 `group3` recordings named `*_abnormal.mp4`, flagged `"abnormal": true`.
  - `real`: 12,000 clips (4,000 takes × 3 views) of 4,000 sentences recorded in real-life indoor/outdoor settings, 3,000 clips per group.
- **Annotations**: Vietnamese sentence (`Sentence`), sign-order gloss sequence (`Sign_sentence`, `|`-separated) and one of 10 categories.

All clips are in a single `train` split; build your own train/val/test split from the metadata.

> [!IMPORTANT]
> All 4,000 `real` sentences also appear in `lab` (same text and `id_sentence`), and each take has 3 views.
> To evaluate on unseen sentences, split by `id_sentence`; to avoid view leakage, keep the 3 views of a take
> (same `scene` and `id_video`) in the same split.

## Splits

| Split | Labeled rows | Found | Missing | Extracted (uploaded) | Failed / empty |
| :--- | ---: | ---: | ---: | ---: | ---: |
| `train` | 84,453 | — | — | 6,000 (extraction in progress) | — |

## Columns

| Column | Type / shape | Description |
| :--- | :--- | :--- |
| `pose_pts` | `float32[T, 33, 3]` | Normalized 3D body pose landmarks (`x, y, z`). |
| `pose_conf` | `float32[T, 33]` | Per-landmark visibility (`0.0` when missing). |
| `face_pts` | `float32[T, 478, 3]` | Normalized 3D face mesh landmarks (incl. iris). |
| `face_conf` | `float32[T, 478]` | `1.0` when the face is detected in the frame, else `0.0`. |
| `left_hand_pts` | `float32[T, 21, 3]` | Normalized 3D left-hand landmarks. |
| `left_hand_conf` | `float32[T, 21]` | `1.0` when the left hand is detected, else `0.0`. |
| `right_hand_pts` | `float32[T, 21, 3]` | Normalized 3D right-hand landmarks. |
| `right_hand_conf` | `float32[T, 21]` | `1.0` when the right hand is detected, else `0.0`. |
| `transcript` | `string` | Vietnamese sentence (NFC-normalized, whitespace-cleaned). |
| `fps` | `float32` | Video frame rate (OpenCV). |
| `duration` | `int32` | Number of decoded frames `T`. |
| `key` | `string` | `train/<Sentence_video_path>`; unique. |
| `metadata` | `string` | JSON object, fields below. |

## Metadata fields

| Field | Type | Description |
| :--- | :--- | :--- |
| `split` | `string` | Always `"train"`. |
| `scene` | `string` | `"lab"` or `"real"`. |
| `filename` | `string` | Video file name. |
| `video_path` | `string` | `Sentence_video_path` from the label CSV (relative to the TriViS root). |
| `id_video` | `int` | Take ID (`ID_video`): the same for the 3 views of a take, unique per take within a scene (not across scenes). |
| `id_sentence` | `int` | Sentence ID (`ID_sentence`); shared between `lab` and `real`. |
| `group` | `string` | Signer group (`"group1"`–`"group4"`). |
| `view` | `string` | `"front"`, `"left"` or `"right"`. |
| `video_belong_id` | `int` | `video_belong_id` column from the label CSV, kept verbatim. |
| `sentence` | `string` | Cleaned Vietnamese sentence. |
| `sign_sentence` | `string` | Gloss sequence as in the CSV (`|`-separated, NFC-normalized). |
| `glosses` | `list[string]` | `sign_sentence` split on `|`. |
| `category` | `string` | One of the 10 categories (case variants in the CSVs are unified). |
| `abnormal` | `bool` | File name ends with `_abnormal.mp4`. |
| `fps` | `float` | Video frame rate. |
| `total_frames` | `int` | Number of decoded frames. |

## Categories

Stored in [`categories.json`](categories.json); the original label CSVs are under [`labels/`](labels/).

- `Cuộc sống thường nhật`
- `Mối quan hệ`
- `Công việc`
- `Du lịch`
- `Cuộc sống học đường`
- `Sức khỏe`
- `Thái độ và Cảm xúc`
- `Tài chính`
- `Chính trị`
- `Văn hóa và Giáo dục`

## Usage

```python
import json
from datasets import load_dataset

ds = load_dataset("Haloroute/TriViS-MediaPipe", split="train")
sample = ds[0]
meta = json.loads(sample["metadata"])
print(sample["transcript"], sample["duration"], meta["scene"], meta["view"], meta["glosses"])
```