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Found 7 papers, 3 papers with code
The Radar Ghost Dataset -- An Evaluation of Ghost Objects in Automotive Radar Data
In this article, we present a dataset with detailed manual annotations for different kinds of ghost detections.
A Benchmark for Spray from Nearby Cutting Vehicles
Current driver assistance systems and autonomous driving stacks are limited to well-defined environment conditions and geo fenced areas.
Using Machine Learning to Detect Ghost Images in Automotive Radar
We show that we can use a state-of-the-art automotive radar classifier in order to detect ghost objects alongside real objects.
Off-the-shelf sensor vs. experimental radar -- How much resolution is necessary in automotive radar classification?
Furthermore, the generalization capabilities of both data sets are evaluated and important comparison metrics for automotive radar object detection are discussed.
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar
In this work, we depart from visible-wavelength approaches and demonstrate detection, classification, and tracking of hidden objects in large-scale dynamic environments using Doppler radars that can be manufactured at low-cost in series production.
Uncertainty Estimation in One-Stage Object Detection
Environment perception is the task for intelligent vehicles on which all subsequent steps rely.
Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather
The fusion of multimodal sensor streams, such as camera, lidar, and radar measurements, plays a critical role in object detection for autonomous vehicles, which base their decision making on these inputs.
Ranked #2 on
2D Object Detection
on Clear Weather
