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 1–10 of 2605 papers

TitleStatusHype
Vision-based Perception for Autonomous Vehicles in Obstacle Avoidance Scenarios—0
Fast and Accurate Collision Probability Estimation for Autonomous Vehicles using Adaptive Sigma-Point Sampling—0
Robustifying 3D Perception through Least-Squares Multi-Agent Graphs Object Tracking—0
LLM-based Realistic Safety-Critical Driving Video Generation—0
A Survey on Vision-Language-Action Models for Autonomous DrivingCode4
Where, What, Why: Towards Explainable Driver Attention PredictionCode1
Coordinated Control of Autonomous Vehicles for Traffic Density Reduction at a Signalized Junction: An MPC Approach—0
Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement—0
AI Safety vs. AI Security: Demystifying the Distinction and Boundaries—0
BIDA: A Bi-level Interaction Decision-making Algorithm for Autonomous Vehicles in Dynamic Traffic Scenarios—0
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Benchmark Results

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