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Survey of unsupervised segmentation in new domains for autonomous driving

Survey of unsupervised segmentation in new domains for autonomous driving


Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving

arXiv paper abstract https://arxiv.org/abs/2304.11928



Deep neural networks (DNNs) ... play a significant role in ... automated driving and are employed for tasks such as detection, semantic segmentation, and sensor fusion.


... generalization of DNNs to new ... domains is a major problem ... methods are required to adapt ... to new domains without labeling ... The task ... is termed unsupervised domain adaptation (UDA).


... the shift between synthetic and real data is of ... importance for automated driving, as it allows the use of simulation environments for DNN training.


... present an overview of the current state of the art in this field of research.


... categorize and explain the different approaches for UDA. The number of considered publications is larger than any other survey on this topic.


... present a quantitative comparison of the approaches and use the observations to point out the latest trends in this field ...



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