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 1481–1490 of 2605 papers

TitleStatusHype
Requirements-driven Test Generation for Autonomous Vehicles with Machine Learning Components—0
RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility in Autonomous Vehicles—0
Residual Graph Convolutional Network for Bird's-Eye-View Semantic Segmentation—0
Resilient Branching MPC for Multi-Vehicle Traffic Scenarios Using Adversarial Disturbance Sequences—0
Resilient Linear Classification: An Approach to Deal with Attacks on Training Data—0
Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference—0
Resource allocation in dynamic multiagent systems—0
Resource-efficient Deep Neural Networks for Automotive Radar Interference Mitigation—0
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems—0
Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment—0
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Benchmark Results

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