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Found 4 papers, 0 papers with code
A Pre-study on Data Processing Pipelines for Roadside Object Detection Systems Towards Safer Road Infrastructure
Single-vehicle accidents are the most common type of fatal accidents in Sweden, where a car drives off the road and runs into hazardous roadside objects.
Building Efficient CNNs Using Depthwise Convolutional Eigen-Filters (DeCEF)
During the analysis, we observe that the effective rank of the vectorized Conv2D filters decreases with respect to the increasing depth in the network, which then leads to the implementation of the Depthwise Convolutional Eigen-Filter (DeCEF) layer.
Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering
In this paper, we aim at filling this gap by developing a multi-object tracking algorithm that takes an image as input and produces trajectories of detected objects in a world coordinate system.
Ranked #16 on
Multiple Object Tracking
on KITTI Tracking test
Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks
The FCN is specifically designed for the task of pixel-wise semantic segmentation by combining a large receptive field with high-resolution feature maps.
