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 441–450 of 2605 papers

TitleStatusHype
Approximate Dynamic Programming for Planning a Ride-Sharing System using Autonomous Fleets of Electric Vehicles—0
Adversarial Patterns: Building Robust Android Malware Classifiers—0
Approaching Neural Network Uncertainty Realism—0
Applying Neural Monte Carlo Tree Search to Unsignalized Multi-intersection Scheduling for Autonomous Vehicles—0
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems—0
A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundabouts—0
Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions—0
A Parameter Adaptive Trajectory Tracking and Motion Control Framework for Autonomous Vehicle—0
Categorical Traffic Transformer: Interpretable and Diverse Behavior Prediction with Tokenized Latent—0
CAT: Closed-loop Adversarial Training for Safe End-to-End Driving—0
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Benchmark Results

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