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Found 6 papers, 4 papers with code
Pedestrian Environment Model for Automated Driving
We only use images from a monocular camera and the vehicle's localization data as input to our pedestrian environment model.
Automated Automotive Radar Calibration With Intelligent Vehicles
We, therefore, present an approach for automated and geo-referenced extrinsic calibration of automotive radar sensors that is based on a novel hypothesis filtering scheme.
Automated Static Camera Calibration with Intelligent Vehicles
Our method does not require any human interaction with the information recorded by both the infrastructure and the vehicle.
Extrinsic Camera Calibration with Semantic Segmentation
Our approach relies on a coarse initial measurement of the camera pose and builds on lidar sensors mounted on a vehicle with high-precision localization to capture a point cloud of the camera environment.
A Spatio-Temporal Multilayer Perceptron for Gesture Recognition
Gesture recognition is essential for the interaction of autonomous vehicles with humans.
Ranked #1 on
Skeleton Based Action Recognition
on Drive&Act
ParticleAugment: Sampling-Based Data Augmentation
By comparing with the related work, our method reaches a balance between the computational cost of policy search and the model performance.
