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 861–870 of 2605 papers

TitleStatusHype
End-to-End 3D Object Detection using LiDAR Point Cloud—0
End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependencies—0
End-to-end Evaluation of Practical Video Analytics Systems for Face Detection and Recognition—0
DeepLaser: Practical Fault Attack on Deep Neural Networks—0
Camera-Radar Perception for Autonomous Vehicles and ADAS: Concepts, Datasets and Metrics—0
End-to-End Lidar-Camera Self-Calibration for Autonomous Vehicles—0
Predictive Planner for Autonomous Driving with Consistency Models—0
End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning—0
End-to-End Steering for Autonomous Vehicles via Conditional Imitation Co-Learning—0
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles—0
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Benchmark Results

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