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 311–320 of 2605 papers

TitleStatusHype
Multimodal Manoeuvre and Trajectory Prediction for Automated Driving on Highways Using Transformer NetworksCode1
Multimodal Object Detection via Probabilistic EnsemblingCode1
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous VehiclesCode1
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
Dense Prediction Transformer for Scale Estimation in Monocular Visual OdometryCode1
Detecting 32 Pedestrian Attributes for Autonomous VehiclesCode1
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under UncertaintyCode1
Keep your Eyes on the Lane: Real-time Attention-guided Lane DetectionCode1
Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning MonitoringCode1
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Benchmark Results

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