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 741–750 of 2605 papers

TitleStatusHype
Autonomous Braking and Throttle System: A Deep Reinforcement Learning Approach for Naturalistic Driving—0
Dissonance Between Human and Machine Understanding—0
Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles—0
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices—0
Distributed Federated Learning for Vehicular Network Security: Anomaly Detection Benefits and Multi-Domain Attack Threats—0
Distributed Learning and Inference with Compressed Images—0
Distributed Observer Design for Tracking Platoon of Connected and Autonomous Vehicles—0
Distributed Radiance Fields for Edge Video Compression and Metaverse Integration in Autonomous Driving—0
Distributed Traffic Control in Complex Dynamic Roadblocks: A Multi-Agent Deep RL Approach—0
Autonomous Algorithm for Training Autonomous Vehicles with Minimal Human Intervention—0
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Benchmark Results

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