Precise facial landmark detection by Dynamic Semantic Aggregation Transformer

Jun Wan, He Liu, Yujia Wu, Zhihui Lai, Wenwen Min, Jun Liu

Abstract: Highlights•This paper aims to learn specialized features to improve face alignment accuracy.•A novel DSA model is designed to activate specific pathways for each sample.•A DSS model is proposed to alleviate semantic ambiguity of multi-scale features.•Our proposed DSAT outperforms SOTA face alignment models.