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.

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 (`
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; the original label CSVs are under 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

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"])