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 11–20 of 2605 papers

TitleStatusHype
Quantum Artificial Intelligence for Secure Autonomous Vehicle Navigation: An Architectural Proposal—0
Semantic and Feature Guided Uncertainty Quantification of Visual Localization for Autonomous Vehicles—0
Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging—0
Mixed Traffic: A Perspective from Long Duration Autonomy—0
Iterative Camera-LiDAR Extrinsic Optimization via Surrogate DiffusionCode0
Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow—0
Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning—0
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications—0
On the Natural Robustness of Vision-Language Models Against Visual Perception Attacks in Autonomous Driving—0
Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario AnalysisCode2
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Benchmark Results

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