Biwi Head Pose Eval

biwi-head-pose-eval

VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction — Vasileiou et al. (2026) (arXiv:2604.10106, 2026)

What this evaluates

Evaluates monocular head pose estimation accuracy by predicting 6DoF rotation (yaw, pitch, roll) from RGB images, comparing absolute single-image regression against relative two-view transformation prediction.

Datasets

• BIWI Kinect Head Pose Database — total ?; splits: test (-1)

Metrics

• MAE (primary) — range: degrees
  • Mean Absolute Error averaged across yaw, pitch, and roll rotation angles. Computed as the average of the absolute differences between predicted and ground-truth angles in degrees.

Input / output format

Input: Single RGB image (absolute mode) or a pair of RGB images consisting of a target frame and an anchor frame with known ground-truth pose (relative mode). Faces are cropped using MTCNN.

Output: Predicted 6DoF head pose rotation specified as yaw, pitch, and roll angles in degrees.

Scoring recipe

def compute_mae(pred_angles, gt_angles):
    # pred_angles, gt_angles: arrays of shape (N, 3) for [yaw, pitch, roll]
    abs_errors = np.abs(pred_angles - gt_angles)
    mae_per_axis = abs_errors.mean(axis=0)
    overall_mae = mae_per_axis.mean()
    return overall_mae

Common pitfalls

• Face detection and cropping strategy must be standardized (MTCNN used here) to ensure fair comparison across baselines.
• Ground-truth poses are originally in the depth-camera frame and must be transformed to the RGB-camera frame using per-subject calibration parameters.
• Relative model performance depends on anchor frame selection; using the first frame of a sequence as a fixed anchor requires only one ground-truth pose per subject.

Evidence (verbatim from paper)

We report mean absolute error (MAE) in degrees for yaw, pitch, and roll, along with the overall MAE averaged across the three axes.

Citation

@misc{vasileiou2026vggthpe,
  title={VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction},
  author={Vasileiou et al. (2026)},
  year={2026},
  note={arXiv:2604.10106}
}

• arXiv: 2604.10106