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 1221–1230 of 2605 papers

TitleStatusHype
Automatic driving lane change safety prediction model based on LSTM—0
DeepLaser: Practical Fault Attack on Deep Neural Networks—0
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles—0
Automatic Calibration of Multiple 3D LiDARs in Urban Environments—0
DeepiSign: Invisible Fragile Watermark to Protect the Integrityand Authenticity of CNN—0
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior—0
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios—0
A machine learning environment for evaluating autonomous driving software—0
DeepFault: Fault Localization for Deep Neural Networks—0
DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks—0
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Benchmark Results

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