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

Showing 341350 of 2605 papers

TitleStatusHype
DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place RecognitionCode1
GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous VehiclesCode1
CenterFusion: Center-based Radar and Camera Fusion for 3D Object DetectionCode1
End-to-end Lane Shape Prediction with TransformersCode1
Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement LearningCode1
Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RLCode1
Keep your Eyes on the Lane: Real-time Attention-guided Lane DetectionCode1
Pedestrian Intention Prediction: A Multi-task PerspectiveCode1
RONELD: Robust Neural Network Output Enhancement for Active Lane DetectionCode1
Neural circuit policies enabling auditable autonomyCode1
Show:102550
← PrevPage 35 of 261Next →

Benchmark Results

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