Self-supervised learning of visual graph matching
Despite the rapid progress made by existing graph matching methods, expensive or even
unrealistic node-level correspondence labels are often required. Inspired by recent progress …
unrealistic node-level correspondence labels are often required. Inspired by recent progress …
Survey on unsupervised domain adaptation for semantic segmentation for visual perception in automated driving
Deep neural networks (DNNs) have proven their capabilities in the past years and play a
significant role in environment perception for the challenging application of automated …
significant role in environment perception for the challenging application of automated …
Augmentation-based Domain Generalization for Semantic Segmentation
M Schwonberg, F El Bouazati… - 2023 IEEE Intelligent …, 2023 - ieeexplore.ieee.org
Unsupervised Domain Adaptation (UDA) and domain generalization (DG) are two research
areas that aim to tackle the lack of generalization of Deep Neural Networks (DNNs) towards …
areas that aim to tackle the lack of generalization of Deep Neural Networks (DNNs) towards …
Combining semantic self-supervision and self-training for domain adaptation in semantic segmentation
J Niemeijer, JP Schäfer - 2021 IEEE Intelligent Vehicles …, 2021 - ieeexplore.ieee.org
This work presents a two-staged, unsupervised domain adaptation process for semantic
segmentation models by combining a self-training and self-supervision strategy. Self …
segmentation models by combining a self-training and self-supervision strategy. Self …