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Datasets/AFLW-19

AFLW-19

The 19 landmark variant of AFLW.

ImagesIntroduced 2016-06-01

The original AFLW provides at most 21 points for each face, but excluding coordinates for invisible landmarks, causing difficulties for training most of the existing baseline approaches. To make fair comparisons, the authors manually annotate the coordinates of these invisible landmarks to enable training of those baseline approaches. The new annotation does not include two ear points because it is very difficult to decide the location of invisible ears. This causes the point number of AFLW-19 to be 19.

The original AFLW does not provide train-test partition. AFLW-19 adopts a partition with 20,000 images for training and 4,386 images for testing (AFLW-Full). In addition, a frontal subset (AFLW-Frontal) is proposed where all landmarks are visible (totally 1,165 images).

The new 19-point annotation file is available at the project page.

Benchmarks

3D/NME_diag (%, Full)3D/NME_diag (%, Frontal)3D/NME_box (%, Full)3D/AUC_box@0.07 (%, Full)3D Face Modelling/NME_diag (%, Full)3D Face Modelling/NME_diag (%, Frontal)3D Face Modelling/NME_box (%, Full)3D Face Modelling/AUC_box@0.07 (%, Full)3D Face Reconstruction/NME_diag (%, Full)3D Face Reconstruction/NME_diag (%, Frontal)3D Face Reconstruction/NME_box (%, Full)3D Face Reconstruction/AUC_box@0.07 (%, Full)Face Reconstruction/NME_diag (%, Full)Face Reconstruction/NME_diag (%, Frontal)Face Reconstruction/NME_box (%, Full)Face Reconstruction/AUC_box@0.07 (%, Full)Facial Recognition and Modelling/NME_diag (%, Full)Facial Recognition and Modelling/NME_diag (%, Frontal)Facial Recognition and Modelling/NME_box (%, Full)Facial Recognition and Modelling/AUC_box@0.07 (%, Full)

Statistics

Papers
24
Benchmarks
20

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Tasks

3D3D Face Modelling3D Face ReconstructionFace AlignmentFace ReconstructionFacial Recognition and Modelling