2023年1月3日 · Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level …

Concretely, for image-level domain shifts, we propose a global photometric alignment module and a global texture alignment module that align images in the source and target domains in terms …

2022年12月14日 · Concretely, for image-level domain shifts, we propose a global photometric alignment module and a global texture alignment module that align images in the source and …

I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation Haoyu Ma §, Xiangru Lin and Yizhou Yu, Fellow, IEEE Abstract—Unsupervised domain adaptation …

Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level image …

Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level image …

2023年1月3日 · Concretely, for image-level domain shifts, we propose a global photometric alignment module and a global texture alignment module that align images in the source and …

2020年12月28日 · 本文在此基础上，交替的迭代更新 F 和 M 网络，以此获取更好的性能。 前向更新就是根据求得的 F 利用一下损失函数更新分割网络 M. 其中第一项对比了迁移之后图像和原 …

This paper proposes the Domain Generalization-Aware Uncertainty Introspective Learning (DGUIL) method, including Potential Uncertainty Modeling (PUM) and Momentum …

I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence ( IF 23.6) Pub Date : 2022-12-14, …