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 1171–1180 of 2605 papers

TitleStatusHype
Interactive Joint Planning for Autonomous Vehicles—0
EqDrive: Efficient Equivariant Motion Forecasting with Multi-Modality for Autonomous Driving—0
Nighttime Driver Behavior Prediction Using Taillight Signal Recognition via CNN-SVM ClassifierCode0
MVFAN: Multi-View Feature Assisted Network for 4D Radar Object Detection—0
Data-driven Traffic Simulation: A Comprehensive Review—0
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency—0
Pre-Training LiDAR-Based 3D Object Detectors Through ColorizationCode0
Augmenting End-to-End Steering Angle Prediction with CAN Bus Data—0
Exploring Driving Behavior for Autonomous Vehicles Based on Gramian Angular Field Vision Transformer—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