DAD-3DHeads: Results

DAD-3D Heads

Dataset

Results

The results of DAD-3DNet trained on DAD-3DHeads Dataset and evaluated on

3D Head Pose Estimation and 3D Face Shape Reconstruction benchmarks,
DAD-3DHeads Benchmark for 3D Head Estimation from dense annotations

suggest that dense supervision as provided in the dataset enables a holistic framework for 3D Head Analysis from images.

3D Head Pose Estimation results

DAD-3DNet largely outperforms the 3DMM estimation methods, and shows comparable performance to other SOTA methods.

BIWI Benchmark

Model

MAE

Pitch MAE

Roll MAE

Yaw MAE

HopeNet

4.90

6.61

3.27

4.81

Img2Pose

3.79

3.55

3.24

4.57

3DDFA-V2

8.81

12.08

7.54

6.80

RingNet

7.34

5.37

7.82

8.82

WHENet

3.81

4.39

3.06

3.99

DAD-3DNet

3.87

5.25

2.77

3.60

BIWI Benchmark

Model

MAE

Pitch MAE

Roll MAE

Yaw MAE

HopeNet

6.16

6.56

5.44

6.74

RetinaNet

6.22

9.64

3.92

5.10

Img2Pose

3.91

5.03

3.28

3.43

SynergyNet

3.35

4.09

2.55

3.42

3DDFA-V2

7.56

8.48

9.89

4.30

RingNet

8.27

4.39

13.51

6.92

DAD-3DNet

3.63

4.73

3.19

2.98

3D Face Shape Reconstruction results

DAD-3DNet shows superior performance to the coarse 3D dense head alignment methods without explicitly disentangling Shape and Expression

NoW Benchmark (to be updated)

Model

Median (mm)

Mean (mm)

Std (mm)

3DDFA-V2

1.234

1.566

1.391

RingNet

1.207

1.535

1.306

DAD-3DNet

1.236

1.541

1.285

NoW Benchmark (to be updated)

Model

3DRMSE

Median - HQ (mm)

Median - LQ (mm)

Mean - HQ (mm)

Mean - LQ (mm)

Std - HQ (mm)

Std - LQ (mm)

3DDFA-V2

2.998

1.500

1.779

1.942

2.350

1.704

2.149

RingNet

2.809

1.698

1.634

2.161

2.113

1.832

1.831

DAD-3DNet

2.718

1.523

1.634

1.957

2.096

1.691

1.808

FEAR:

Fast, Efficient, Accurate and Robust Visual Tracker

VGGHeads

A Large-Scale Synthetic Dataset for 3D Human Heads

Dataset Enhancement

with Instance-Level Augmentations

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