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 251–260 of 2605 papers

TitleStatusHype
Optimal Robust Network Design: Formulations and Algorithms for Maximizing Algebraic ConnectivityCode1
Efficient Reinforcement Learning via Decoupling Exploration and UtilizationCode1
Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RLCode1
ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement LearningCode1
Detection-segmentation convolutional neural network for autonomous vehicle perceptionCode1
CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic SegmentationCode1
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud DataCode1
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?Code1
Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous VehiclesCode1
CAVIAR: Co-simulation of 6G Communications, 3D Scenarios and AI for Digital TwinsCode1
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Benchmark Results

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