MERL-RAV

MERL Reannotation of AFLW with Visibility

Dataset Information
Modalities
Images
Introduced
2020
License
Unknown
Homepage
Official Website
Contents

Overview

The MERL-RAV (MERL Reannotation of AFLW with Visibility) Dataset contains over 19,000 face images in a full range of head poses. Each face is manually labeled with the ground-truth locations of 68 landmarks, with the additional information of whether each landmark is unoccluded, self-occluded (due to extreme head poses), or externally occluded. The images were annotated by professional labelers, supervised by researchers at Mitsubishi Electric Research Laboratories (MERL).

Variants: MERL-RAV

Associated Benchmarks

This dataset is used in 1 benchmark:

  • Pose Estimation - Metrics: MAE mean (º), MAE yaw (º), MAE pitch (º), MAE roll (º)

Recent Benchmark Submissions

Task Model Paper Date
Pose Estimation SPIGA Shape Preserving Facial Landmarks with … 2022-10-13

Research Papers

Recent papers with results on this dataset:

External Links: