8 citations · 19 across the 10 of their papers we have counts for
10 papers
DMSA: Dynamic Multi-scale Unsupervised Semantic Segmentation Based on Adaptive Affinity
Kun Yang, Jun Lu
The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions. The framework uses Atrous Spatial Pyrami…
Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model
Lingsheng Kong, Bo Hu, Xiongchang Liu +3
Deep learning is usually data starved, and the unsupervised domain adaptation (UDA) is developed to introduce the knowledge in the labeled source domain to the unlabeled target dom…
Subtype-Aware Dynamic Unsupervised Domain Adaptation
Xiaofeng Liu, Fangxu Xing, Jia You +4
Unsupervised domain adaptation (UDA) has been successfully applied to transfer knowledge from a labeled source domain to target domains without their labels. Recently introduced tr…
Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation
Xiaofeng Liu, Site Li, Yubin Ge +3
The unsupervised domain adaptation (UDA) has been widely adopted to alleviate the data scalability issue, while the existing works usually focus on classifying independently discre…
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference
Xiaofeng Liu, Bo Hu, Linghao Jin +6
In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training…
Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis
Xiaofeng Liu, Xiongchang Liu, Bo Hu +7
Recent advances in unsupervised domain adaptation (UDA) show that transferable prototypical learning presents a powerful means for class conditional alignment, which encourages the…