no code implementations • ICCV 2023 • Qipeng Liu, Luojun Lin, Zhifeng Shen, Zhifeng Yang
To address this issue, we propose the Periodically Exchange Teacher-Student (PETS) method, a simple yet novel approach that introduces a multiple-teacher framework consisting of a static teacher, a dynamic teacher, and a student model.
1 code implementation • 23 Nov 2023 • Luojun Lin, Zhifeng Shen, Jia-Li Yin, Qipeng Liu, Yuanlong Yu, WeiJie Chen
To this end, we propose a novel MetaFBP framework, in which we devise a universal feature extractor to capture the aesthetic commonality and then optimize to adapt the aesthetic individuality by shifting the decision boundary of the predictor via a meta-learning mechanism.