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 1411–1420 of 2605 papers

TitleStatusHype
Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning—0
Probabilistic Prediction of Vehicle Semantic Intention and Motion—0
Probabilistic Segmentation for Robust Field of View Estimation—0
Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process—0
Probabilistic Uncertainty-Aware Risk Spot Detector for Naturalistic Driving—0
Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications—0
Proceedings First Workshop on Formal Verification of Autonomous Vehicles—0
Prospective Role of Foundation Models in Advancing Autonomous Vehicles—0
Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea—0
Providentia -- A Large-Scale Sensor System for the Assistance of Autonomous Vehicles and Its Evaluation—0
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Benchmark Results

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