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 891–900 of 2605 papers

TitleStatusHype
Data-driven Traffic Simulation: A Comprehensive Review—0
Safe Navigation: Training Autonomous Vehicles using Deep Reinforcement Learning in CARLACode1
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
KI-PMF: Knowledge Integrated Plausible Motion Forecasting—0
Classification of Safety Driver Attention During Autonomous Vehicle Operation—0
LiDAR-based 4D Occupancy Completion and ForecastingCode1
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Benchmark Results

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