71 citations · 82 across the 5 of their papers we have counts for
5 papers
Exploring Model Transferability through the Lens of Potential Energy
Xiaotong Li, Zixuan Hu, Yixiao Ge +2
Transfer learning has become crucial in computer vision tasks due to the vast availability of pre-trained deep learning models. However, selecting the optimal pre-trained model fro…
Modeling Uncertain Feature Representation for Domain Generalization
Xiaotong Li, Zixuan Hu, Jun Liu +3
Though deep neural networks have achieved impressive success on various vision tasks, obvious performance degradation still exists when models are tested in out-of-distribution sce…
Uncertainty Modeling for Out-of-Distribution Generalization
Xiaotong Li, Yongxing Dai, Yixiao Ge +3
Though remarkable progress has been achieved in various vision tasks, deep neural networks still suffer obvious performance degradation when tested in out-of-distribution scenarios…
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
Haoran Wang, Tong Shen, Wei Zhang +2
Despite great progress in supervised semantic segmentation,a large performance drop is usually observed when deploying the model in the wild. Domain adaptation methods tackle the i…
Hard-Aware Fashion Attribute Classification
Yun Ye, Yixin Li, Bo Wu +3
Fashion attribute classification is of great importance to many high-level tasks such as fashion item search, fashion trend analysis, fashion recommendation, etc. The task is chall…