SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

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Showing 1041–1050 of 2605 papers

TitleStatusHype
Convergence of Communications, Control, and Machine Learning for Secure and Autonomous Vehicle Navigation—0
Exploiting Richness of Learned Compressed Representation of Images for Semantic Segmentation—0
Multi-Predictor Fusion: Combining Learning-based and Rule-based Trajectory Predictors—0
UnLoc: A Universal Localization Method for Autonomous Vehicles using LiDAR, Radar and/or Camera Input—0
Locking On: Leveraging Dynamic Vehicle-Imposed Motion Constraints to Improve Visual Localization—0
Detection-segmentation convolutional neural network for autonomous vehicle perceptionCode1
Comparative study of subset selection methods for rapid prototyping of 3D object detection algorithmsCode0
A Survey on Datasets for Decision-making of Autonomous Vehicle—0
Action and Trajectory Planning for Urban Autonomous Driving with Hierarchical Reinforcement Learning—0
CARMA: Context-Aware Runtime Reconfiguration for Energy-Efficient Sensor Fusion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified