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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1471–1480 of 2605 papers

TitleStatusHype
Reinforced Wasserstein Training for Severity-Aware Semantic Segmentation in Autonomous Driving—0
Reinforcement Learning-based Optimal Control and Software Rejuvenation for Safe and Efficient UAV Navigation—0
Reinforcement Learning-Enabled Decision-Making Strategies for a Vehicle-Cyber-Physical-System in Connected Environment—0
Reinforcement Learning for Freeway Lane-Change Regulation via Connected Vehicles—0
Reinforcement Learning for Joint V2I Network Selection and Autonomous Driving Policies—0
Reinforcement Learning in Conflicting Environments for Autonomous Vehicles—0
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic—0
Reliability Analysis of Artificial Intelligence Systems Using Recurrent Events Data from Autonomous Vehicles—0
Reliable, Routable, and Reproducible: Collection of Pedestrian Pathways at Statewide Scale—0
RePLAy: Remove Projective LiDAR Depthmap Artifacts via Exploiting Epipolar Geometry—0
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Benchmark Results

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