7 citations · 21 across the 7 of their papers we have counts for
7 papers · 1 filter
Distilling Vision-Language Foundation Models: A Data-Free Approach via Prompt Diversification
Yunyi Xuan, Weijie Chen, Shicai Yang +3
Data-Free Knowledge Distillation (DFKD) has shown great potential in creating a compact student model while alleviating the dependency on real training data by synthesizing surroga…
MetaFBP: Learning to Learn High-Order Predictor for Personalized Facial Beauty Prediction
Luojun Lin, Zhifeng Shen, Jia-Li Yin +3
Predicting individual aesthetic preferences holds significant practical applications and academic implications for human society. However, existing studies mainly focus on learning…
Parameter Exchange for Robust Dynamic Domain Generalization
Luojun Lin, Zhifeng Shen, Zhishu Sun +3
Agnostic domain shift is the main reason of model degradation on the unknown target domains, which brings an urgent need to develop Domain Generalization (DG). Recent advances at D…
Adapt Anything: Tailor Any Image Classifiers across Domains And Categories Using Text-to-Image Diffusion Models
Weijie Chen, Haoyu Wang, Shicai Yang +6
We do not pursue a novel method in this paper, but aim to study if a modern text-to-image diffusion model can tailor any task-adaptive image classifier across domains and categorie…
Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation
Weijie Chen, Luojun Lin, Shicai Yang +4
It is a strong prerequisite to access source data freely in many existing unsupervised domain adaptation approaches. However, source data is agnostic in many practical scenarios du…
Unsupervised Image Classification for Deep Representation Learning
Weijie Chen, Shiliang Pu, Di Xie +3
Deep clustering against self-supervised learning is a very important and promising direction for unsupervised visual representation learning since it requires little domain knowled…