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 1931–1940 of 2605 papers

TitleStatusHype
CGAP2: Context and gap aware predictive pose framework for early detection of gestures—0
Assessment of System-Level Cyber Attack Vulnerability for Connected and Autonomous Vehicles Using Bayesian Networks—0
DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place RecognitionCode1
Efficient falsification approach for autonomous vehicle validation using a parameter optimisation technique based on reinforcement learning—0
GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous VehiclesCode1
Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Loss—0
CenterFusion: Center-based Radar and Camera Fusion for 3D Object DetectionCode1
Model-based Reinforcement Learning from Signal Temporal Logic Specifications—0
End-to-end Lane Shape Prediction with TransformersCode1
Multi-Agent Reinforcement Learning for Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems—0
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Benchmark Results

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