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Found 4 papers, 2 papers with code
3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods
Transforming the raw point cloud data into a dense 2D matrix structure is a promising way for applying compression algorithms.
Enhancing Lidar-based Object Detection in Adverse Weather using Offset Sequences in Time
Our findings demonstrate that our novel method, involving temporal offset augmentation through randomized frame skipping in sequences, enhances object detection accuracy compared to both the baseline model (Pillar-based Object Detection) and no augmentation.
A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird's Eye View
Accurate environment perception is essential for automated driving.
Ranked #1 on
Semantic Segmentation
on Cam2BEV
Bird View Synthesis
Cross-View Image-to-Image Translation
+2
Reducing Uncertainty by Fusing Dynamic Occupancy Grid Maps in a Cloud-based Collective Environment Model
This paper describes a method to combine perception data of automated and connected vehicles in the form of evidential Dynamic Occupany Grid Maps (DOGMas) in a cloud-based system.
