4 citations · 4 across the 5 of their papers we have counts for
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cs.CV2023
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…
cs.CV2022
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…
cs.CV2022
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…