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 181–190 of 2605 papers

TitleStatusHype
Enhancing Safety in Mixed Traffic: Learning-Based Modeling and Efficient Control of Autonomous and Human-Driven VehiclesCode1
ERMVP: Communication-Efficient and Collaboration-Robust Multi-Vehicle Perception in Challenging EnvironmentsCode1
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud DataCode1
Explaining Autonomous Driving Actions with Visual Question AnsweringCode1
Extrapolated Urban View Synthesis BenchmarkCode1
Fast and Efficient Transformer-based Method for Bird's Eye View Instance PredictionCode1
Fast nonlinear risk assessment for autonomous vehicles using learned conditional probabilistic models of agent futuresCode1
Fast Risk Assessment for Autonomous Vehicles Using Learned Models of Agent FuturesCode1
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy TrafficCode1
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?Code1
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Benchmark Results

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