aflw2k3d

AFLW2000-3D is a dataset of 2000 images that have been annotated with image-level 68-point 3D facial landmarks. This dataset is typically 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. The 2D landmarks are skipped in this dataset, since some of the data are not consistent to 21 points, as the original paper mentioned.

• URL: http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm
• DatasetBuilder: tfds.image.aflw2k3d.Aflw2k3d
• Version: v1.0.0

• Versions:

  • 1.0.0 (default):

• Size: 83.36 MiB

Features

FeaturesDict({
    'image': Image(shape=(450, 450, 3), dtype=tf.uint8),
    'landmarks_68_3d_xy_normalized': Tensor(shape=(68, 2), dtype=tf.float32),
    'landmarks_68_3d_z': Tensor(shape=(68, 1), dtype=tf.float32),
})

Statistics

Homepage

• http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm

Citation

@article{DBLP:journals/corr/ZhuLLSL15,
  author    = {Xiangyu Zhu and
               Zhen Lei and
               Xiaoming Liu and
               Hailin Shi and
               Stan Z. Li},
  title     = {Face Alignment Across Large Poses: {A} 3D Solution},
  journal   = {CoRR},
  volume    = {abs/1511.07212},
  year      = {2015},
  url       = {http://arxiv.org/abs/1511.07212},
  archivePrefix = {arXiv},
  eprint    = {1511.07212},
  timestamp = {Mon, 13 Aug 2018 16:48:23 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/ZhuLLSL15},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}