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Found 3 papers, 2 papers with code
End-To-End multi-modal sensors fusion system for urban automated driving
In this paper, we present a novel framework for urban automated driving based on multi-modal sensors; LiDAR and Camera.
ShuffleSeg: Real-time Semantic Segmentation Network
It is shown that skip architecture in the decoding method provides the best compromise for the goal of real-time performance, while it provides adequate accuracy by utilizing higher resolution feature maps for a more accurate segmentation.
RTSeg: Real-time Semantic Segmentation Comparative Study
In this paper, we address this gap by presenting a real-time semantic segmentation benchmarking framework with a decoupled design for feature extraction and decoding methods.
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