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 861–870 of 2605 papers

TitleStatusHype
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning—0
Simultaneous Clutter Detection and Semantic Segmentation of Moving Objects for Automotive Radar Data—0
Trajectories and Platoon-forming Algorithm for Intersections with Heterogeneous Autonomous Traffic—0
Optimising Human-AI Collaboration by Learning Convincing Explanations—0
Investigating Robustness in Cyber-Physical Systems: Specification-Centric Analysis in the face of System Deviations—0
Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach—0
Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference—0
MonoProb: Self-Supervised Monocular Depth Estimation with Interpretable UncertaintyCode1
Automated Lane Change via Adaptive Interactive MPC: Human-in-the-Loop ExperimentsCode1
RobustMat: Neural Diffusion for Street Landmark Patch Matching under Challenging EnvironmentsCode0
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Benchmark Results

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