facial landmark datection-数据集

人脸特征点数据集，主要包括：性别，是否带眼睛，是否微笑和脸部姿势。

Facial landmark detection of face alignment has long been impeded by the problems of occlusion and pose variation. Instead of treating the detection task as a single and independent problem, we investigate the possibility of improving detection robustness through multi-task learning. Specifically, we wish to optimize facial landmark detection together with heterogeneous but subtly correlated tasks, e.g., head pose estimation and facial attribute inference. This is non-trivial since different tasks have different learning difficulties and convergence rates. To address this problem, we formulate a novel tasks-constrained deep model, with task-wise early stopping to facilitate learning convergence. Extensive evaluations show that the proposed task-constrained learning (i) outperforms existing methods, especially in dealing with faces with severe occlusion and pose variation, and (ii) reduces model complexity drastically compared to the state-of-the-art method based on cascaded deep model.

译：

长期以来，由于遮挡和姿态变化等问题，人脸定位中的标志点检测一直受到阻碍。我们研究了通过多任务学习提高检测鲁棒性的可能性，而不是将检测任务看作一个单独的独立问题。具体地说，我们希望将面部标志点检测与异构但微妙相关的任务（如头部姿势估计和面部属性推断）一起优化。这是非常重要的，因为不同的任务有不同的学习困难和收敛速度。为了解决这一问题，我们提出了一个新的任务约束深度模型，通过任务提前停止来促进学习收敛。与现有的基于深度遮挡模型的方法相比，该方法能显著降低复杂度。

大家可以到官网地址下载数据集，我自己也在百度网盘分享了一份。可关注本人公众号，回复“2020082801”获取下载链接。

只要自己有时间，都尽量写写文章，与大家交流分享。

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CSDN博客地址：https://blog.csdn.net/ispeasant