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 1041–1050 of 2605 papers

TitleStatusHype
A New Adversarial Perspective for LiDAR-based 3D Object Detection—0
Driving with Regulation: Interpretable Decision-Making for Autonomous Vehicles with Retrieval-Augmented Reasoning via LLM—0
Benefits of V2V communication in connected and autonomous vehicles in the presence of delays in communicated signals—0
Driving with Prior Maps: Unified Vector Prior Encoding for Autonomous Vehicle Mapping—0
Driving Towards Inclusion: A Systematic Review of AI-powered Accessibility Enhancements for People with Disability in Autonomous Vehicles—0
Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators—0
An Evaluation of RGB and LiDAR Fusion for Semantic Segmentation—0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
A Comparative Analysis of Machine Learning Methods for Lane Change Intention Recognition Using Vehicle Trajectory Data—0
Driving Tasks Transfer in Deep Reinforcement Learning for Decision-making of Autonomous Vehicles—0
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Benchmark Results

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