Keypoints and gloss annotations, numpy-ready. No raw video ships: signers stay
pseudonymized, and every number on this page is reproducible from the download.
QUICK START · PYTHONmetadata.csv · keypoints/*.npy
from huggingface_hub import snapshot_download
import numpy as np, pandas as pd
root = snapshot_download(repo_id="CLERC-DATA/epee", repo_type="dataset")
meta = pd.read_csv(f"{root}/metadata.csv")
# five renderings of the same phrase, ready to compare
phrase = meta[(meta.parallel == "yes") & (meta.phrase_id == 7)]
clips = {r.signer_id: np.load(f"{root}/keypoints/{r.clip_id}.npy")
for r in phrase.itertuples()} # each (n_frames, 128, 3)
Research and evaluation are free under CC BY-NC-SA 4.0, with attribution and the DOI.
The larger CLERC corpus, growing weekly, is licensed commercially as keypoints and
annotations, never as video:
florian@clerc.io