Personalized Image Aesthetic Evaluation Method Based on Dual Attention Mechanism and Meta-Transfer Learning
Personalized image aesthetic evaluation has been widely used for perception evaluation of different users'personalized aesthetic differences.However,the existing popular image aesthetic model can not adapt well to the small sample personalized image aesthetic evaluation task.To solve this problem,this paper proposes the dual attention Efficient-Net network and meta-learning PIAA method(DA-EBLG-PIAA),which combine the personalized ratings of a single user in-to different single tasks respectively.The EfficientNet network serves as the backbone network to accommodate small sam-ple learning tasks.The dual attention mechanism is integrated to better capture the global feature dependencies in space and channel dimensions.The experimental results show that the performance of the proposed personalized aesthetic evalu-ation method is better than many existing models and can be effectively applied to the aesthetic perception evaluation of personalized images.
万方数据
维普
