3D Face Reconstruction On Aflw2000 3D

Metrics

Mean NME

Results

Performance results of various models on this benchmark

		Paper Title
DeFA	5.6454%	Dense Face Alignment
3DDFA	5.3695%	Face Alignment Across Large Poses: A 3D Solution
PRN	3.9625%	Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
3DDFA-V2	3.56%	Towards Fast, Accurate and Stable 3D Dense Face Alignment
B-spline FFD	3.51%	Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images
VGG-F	3.42%	Pre-training strategies and datasets for facial representation learning
SADRNet	3.25%	SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
DSFNet-is	-	DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment

0 of 8 row(s) selected.

3D Face Reconstruction On Aflw2000 3D

Metrics

Mean NME

Results

Performance results of various models on this benchmark

		Paper Title
DeFA	5.6454%	Dense Face Alignment
3DDFA	5.3695%	Face Alignment Across Large Poses: A 3D Solution
PRN	3.9625%	Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
3DDFA-V2	3.56%	Towards Fast, Accurate and Stable 3D Dense Face Alignment
B-spline FFD	3.51%	Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images
VGG-F	3.42%	Pre-training strategies and datasets for facial representation learning
SADRNet	3.25%	SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
DSFNet-is	-	DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment

0 of 8 row(s) selected.

3D Face Reconstruction On Aflw2000 3D | SOTA | HyperAI