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 981–990 of 2605 papers

TitleStatusHype
Feature Analysis and Selection for Training an End-to-End Autonomous Vehicle Controller Using the Deep Learning Approach—0
Feature Importance in Pedestrian Intention Prediction: A Context-Aware Review—0
Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities—0
Federated Data-Driven Kalman Filtering for State Estimation—0
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning—0
Federated Feature Selection for Cyber-Physical Systems of Systems—0
A Brief Survey on Autonomous Vehicle Possible Attacks, Exploits and Vulnerabilities—0
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions—0
Automated design of error-resilient and hardware-efficient deep neural networks—0
Decision-Making Technology for Autonomous Vehicles Learning-Based Methods, Applications and Future Outlook—0
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Benchmark Results

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