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AFLW2K3D
创建来自Hello Dataset / Robert
概要
活动

Overview

We propose a solution to the three problems in an new alignment framework, called 3D Dense Face Alignment (3DDFA), in which a dense 3D face model is fitted to the image via convolutional neutral network (CNN). We also propose a method to synthesize large-scale training samples in profile views to solve the third problem of data labelling. Experiments on the challenging AFLW database show that our approach achieves significant improvements over state-of-the-art methods.

Citation

Please use the following citation when referencing the dataset:

@inproceedings{zhu2016face,
  title={Face alignment across large poses: A 3d solution},
  author={Zhu, Xiangyu and Lei, Zhen and Liu, Xiaoming and Shi, Hailin and Li, Stan Z},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={146--155},
  year={2016}
}
数据集信息
应用场景Face
标注类型Keypoints3D
LicenseUnknown
更新时间2021-03-24 22:56:51
数据概要
数据格式Image
数据数量0
文件大小5MB
标注数量0
版权归属方
Institute of Automation, Chinese Academy of Sciences
标注方
未知
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相关数据集
AFLW
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