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Found 3 papers, 1 papers with code
DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans
To make the predictions from the DCNN temporally consistent, we propose a Bayes filter based method.
Learning a Local Feature Descriptor for 3D LiDAR Scans
Our proposed architecture consists of a Siamese network for learning a feature descriptor and a metric learning network for matching the descriptors.
Deep Semantic Classification for 3D LiDAR Data
To learn the distinction between movable and non-movable points in the environment, we introduce an approach based on deep neural network and for detecting the dynamic points, we estimate pointwise motion.
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