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 221–230 of 2605 papers

TitleStatusHype
Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-SupervisionCode1
Learning Cooperative Trajectory Representations for Motion ForecastingCode1
Continual Driving Policy Optimization with Closed-Loop Individualized CurriculaCode1
AoSRNet: All-in-One Scene Recovery Networks via Multi-knowledge IntegrationCode1
MSMA: Multi-agent Trajectory Prediction in Connected and Autonomous Vehicle Environment with Multi-source Data IntegrationCode1
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement LearningCode1
CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic SegmentationCode1
Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous VehiclesCode1
LOPR: Latent Occupancy PRediction using Generative ModelsCode1
A Baseline for the Commands For Autonomous Vehicles ChallengeCode1
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Benchmark Results

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