- Description:
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.
Homepage: http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm
Source code:
tfds.image.Aflw2k3d
Versions:
1.0.0
(default): No release notes.
Download size:
83.36 MiB
Dataset size:
Unknown size
Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'train' |
2,000 |
- 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),
})
Supervised keys (See
as_supervised
doc):None
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}
}
- Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):