Research on facial landmark detection algorithm based on improved attention mechanism

Abstract

In recent years, facial landmark detection has assumed an important role in various fields. However, the current facial landmark detection algorithms are still lacking in recognition accuracy. In order to solve the above problem, this paper uses Ghost bottleneck to replace the original bottleneck on the basis of the original model of PFLD model, and adds and improves the CBAM attention mechanism. The improved PFLD model increases the ability of the model to extract facial landmark and improves the accuracy of the algorithm. The improved model has high accuracy and low parametric number and improves the accuracy of facial landmark detection. It also provides a new idea for facial landmark detection task.

Revitalizing Convolutional Network for Image Restoration

“…(b) Spatial attention. Spatial attention facilitates models to attend to the important region, which is useful for handling spatially-varying blurs [11], [21], [22]. (c) Frequency modulation.…”