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Found 4 papers, 1 papers with code
MKConv: Multidimensional Feature Representation for Point Cloud Analysis
In this paper, we present Multidimensional Kernel Convolution (MKConv), a novel convolution operator that learns to transform the point feature representation from a vector to a multidimensional matrix.
Ranked #13 on
3D Part Segmentation
on ShapeNet-Part
Robust Lane Detection via Expanded Self Attention
Modern deep learning methods achieve high performance in lane detection, but it is still difficult to accurately detect lanes in challenging situations such as congested roads and extreme lighting conditions.
Ranked #42 on
Lane Detection
on CULane
False Positive Removal for 3D Vehicle Detection with Penetrated Point Classifier
Recently, researchers have been leveraging LiDAR point cloud for higher accuracy in 3D vehicle detection.
Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs
Experiments conducted with a dataset that we collect in a mock-up car environment demonstrate that the proposed InterCNN with MobileNet convolutional blocks can classify 9 different behaviors with 73. 97% accuracy, and 5 'aggregated' behaviors with 81. 66% accuracy.
