3 citations · 4 across the 4 of their papers we have counts for
5 papers · 1 filter
Unsupervised Prototype Adapter for Vision-Language Models
Yi Zhang, Ce Zhang, Xueting Hu +1
Recently, large-scale pre-trained vision-language models (e.g. CLIP and ALIGN) have demonstrated remarkable effectiveness in acquiring transferable visual representations. To lever…
Cross-Modal Concept Learning and Inference for Vision-Language Models
Yi Zhang, Ce Zhang, Yushun Tang +1
Large-scale pre-trained Vision-Language Models (VLMs), such as CLIP, establish the correlation between texts and images, achieving remarkable success on various downstream tasks wi…
Cross-Inferential Networks for Source-free Unsupervised Domain Adaptation
Yushun Tang, Qinghai Guo, Zhihai He
One central challenge in source-free unsupervised domain adaptation (UDA) is the lack of an effective approach to evaluate the prediction results of the adapted network model in th…
Contrastive Bayesian Analysis for Deep Metric Learning
Shichao Kan, Zhiquan He, Yigang Cen +3
Recent methods for deep metric learning have been focusing on designing different contrastive loss functions between positive and negative pairs of samples so that the learned feat…
Coded Residual Transform for Generalizable Deep Metric Learning
Shichao Kan, Yixiong Liang, Min Li +3
A fundamental challenge in deep metric learning is the generalization capability of the feature embedding network model since the embedding network learned on training classes need…