With the development of deep learning, the perception of facial image has wide prospects of
application. In a crowded environment, there is a problem that faces cannot be detected due …

Nowadays, the number of Internet image data is increasing rapidly, so it is urgent to
understand image information by corresponding intelligent system. The purpose of face …

The detection of multiple faces in unconstrained environment in deep learning suffers from
insufficient detection accuracy and inefficiency; at the same time, the detection of blurred …

In recent years, the application of visual processing algorithm based on deep network on
mobile terminal has become a popular research problem. In this paper, a new face loss …

The practical application requires a vision-based face detector to work in real-time. The
robot application uses the face detection method as the initial process for the face analysis …

In view of the insufficient use of the semantic information of high-level feature maps under
the existing face detection algorithms, resulting in unsatisfactory face detection results in …

With the rapid development of artificial intelligence, face detection technology is widely used
in our daily lives, such as mobile payment, video conferencing and personal identification …

Faster R-CNN is a popular method in object detection applications. Based on the similar
characteristics of the category in face detection and the category label of target background …

Face recognition technology has been widely studied and applied for decades, and deep
neural networks have greatly improved the indicators of face recognition systems. However …

With the continuous development of deep learning in the fields of security, smart retail, and
smart home, etc., face detection algorithm has become a key technology and been widely …