1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2020
Robust Semantic Segmentation in Adverse Weather Conditions by means of Fast Video-Sequence Segmentation
Andreas Pfeuffer, Klaus Dietmayer
Computer vision tasks such as semantic segmentation perform very well in good weather conditions, but if the weather turns bad, they have problems to achieve this performance in th…
cs.CV2019
Separable Convolutional LSTMs for Faster Video Segmentation
Andreas Pfeuffer, Klaus Dietmayer
Semantic Segmentation is an important module for autonomous robots such as self-driving cars. The advantage of video segmentation approaches compared to single image segmentation i…
cs.CV2019★ 1 cited
Robust Semantic Segmentation in Adverse Weather Conditions by means of Sensor Data Fusion
Andreas Pfeuffer, Klaus Dietmayer
A robust and reliable semantic segmentation in adverse weather conditions is very important for autonomous cars, but most state-of-the-art approaches only achieve high accuracy rat…