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 1961–1970 of 2605 papers

TitleStatusHype
Prediction-Based GNSS Spoofing Attack Detection for Autonomous Vehicles—0
Transportation Internet: Concepts, Models, and Architectures—0
On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation—0
Neural circuit policies enabling auditable autonomyCode1
Audio-Visual Self-Supervised Terrain Type Discovery for Mobile Platforms—0
A Cooperative Control Framework for CAV Lane Change in a Mixed Traffic Environment—0
Using Empirical Trajectory Data to Design Connected Autonomous Vehicle Controllers for Traffic Stabilization—0
Leveraging the Capabilities of Connected and Autonomous Vehicles and Multi-Agent Reinforcement Learning to Mitigate Highway Bottleneck Congestion—0
Autonomous Vehicle Visual Signals for Pedestrians: Experiments and Design Recommendations—0
Robust Behavioral Cloning for Autonomous Vehicles using End-to-End Imitation LearningCode1
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Benchmark Results

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