AFLW2000-3D is a dataset of 2000 images that have been annotated with image-level 68-point 3D facial landmarks. This dataset is used for evaluation of 3D facial landmark detection models. The head poses are very diverse and often hard to be detected by a CNN-based face detector.
Source: https://www.tensorflow.org/datasets/catalog/aflw2k3d
Image Source: http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm
Variants: AFLW2000, AFLW2000-3D
This dataset is used in 2 benchmarks:
Task | Model | Paper | Date |
---|---|---|---|
3D Face Reconstruction | DSFNet-is | DSFNet: Dual Space Fusion Network … | 2023-05-19 |
3D Face Reconstruction | SADRNet | SADRNet: Self-Aligned Dual Face Regression … | 2021-06-06 |
3D Face Reconstruction | B-spline FFD | Learning Free-Form Deformation for 3D … | 2021-05-31 |
3D Face Reconstruction | VGG-F | Pre-training strategies and datasets for … | 2021-03-30 |
3D Face Reconstruction | 3DDFA-V2 | Towards Fast, Accurate and Stable … | 2020-09-21 |
3D Face Reconstruction | PRN | Joint 3D Face Reconstruction and … | 2018-03-21 |
Facial Landmark Detection | JVCR | Joint Voxel and Coordinate Regression … | 2018-01-28 |
3D Face Reconstruction | DeFA | Dense Face Alignment | 2017-09-05 |
3D Face Reconstruction | 3DDFA | Face Alignment Across Large Poses: … | 2015-11-23 |
Recent papers with results on this dataset: