Search Results for author:
Found 8 papers, 4 papers with code
Learning to Predict Navigational Patterns from Partial Observations
We demonstrate how to infer global navigational patterns by fitting a maximum likelihood graph to the DSLP field.
Ranked #1 on
Lane Detection
on nuScenes
Predictive World Models from Real-World Partial Observations
By extending HVAEs to cases where complete ground truth states do not exist, we facilitate continual learning of spatial prediction as a step towards realizing explainable and comprehensive predictive world models for real-world mobile robotics applications.
RSG-Net: Towards Rich Sematic Relationship Prediction for Intelligent Vehicle in Complex Environments
Behavioral and semantic relationships play a vital role on intelligent self-driving vehicles and ADAS systems.
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment
Recent self-supervised models have demonstrated equal or better performance than supervised methods, opening for AI systems to learn visual representations from practically unlimited data.
Ranked #1 on
Unsupervised Semantic Segmentation
on COCO-Stuff-27
Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset for Intelligent Vehicles
And this provides us a great opportunity to think about how shall these data be organized and exploited.
Characterization of Multiple 3D LiDARs for Localization and Mapping using Normal Distributions Transform
In this work, we present a detailed comparison of ten different 3D LiDAR sensors, covering a range of manufacturers, models, and laser configurations, for the tasks of mapping and vehicle localization, using as common reference the Normal Distributions Transform (NDT) algorithm implemented in the self-driving open source platform Autoware.
LIBRE: The Multiple 3D LiDAR Dataset
In this work, we present LIBRE: LiDAR Benchmarking and Reference, a first-of-its-kind dataset featuring 10 different LiDAR sensors, covering a range of manufacturers, models, and laser configurations.
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience.
Robotics Systems and Control Systems and Control
