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
Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and PriorsCode1
InconSeg: Residual-Guided Fusion With Inconsistent Multi-Modal Data for Negative and Positive Road Obstacles SegmentationCode1
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
SMART: A Decision-Making Framework with Multi-modality Fusion for Autonomous Driving Based on Reinforcement LearningCode1
HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformerCode1
Optimal Robust Network Design: Formulations and Algorithms for Maximizing Algebraic ConnectivityCode1
RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario UnderstandingCode1
PCPNet: An Efficient and Semantic-Enhanced Transformer Network for Point Cloud PredictionCode1
Multimodal Manoeuvre and Trajectory Prediction for Automated Driving on Highways Using Transformer NetworksCode1
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Benchmark Results

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