34 citations · 65 across the 22 of their papers we have counts for
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cs.CV2022★ 10 cited
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
Lukas Hoyer, Dengxin Dai, Haoran Wang +1
In unsupervised domain adaptation (UDA), a model trained on source data (e.g. synthetic) is adapted to target data (e.g. real-world) without access to target annotation. Most previ…
cs.CV2022★ 7 cited
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
Lukas Hoyer, Dengxin Dai, Luc Van Gool
Unsupervised domain adaptation (UDA) aims to adapt a model trained on the source domain (e.g. synthetic data) to the target domain (e.g. real-world data) without requiring further…