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 681–690 of 2605 papers

TitleStatusHype
CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening—0
A Parameter Adaptive Trajectory Tracking and Motion Control Framework for Autonomous Vehicle—0
End-to-End Steering for Autonomous Vehicles via Conditional Imitation Co-Learning—0
Generating Out-Of-Distribution Scenarios Using Language Models—0
Enhancing Object Detection Accuracy in Autonomous Vehicles Using Synthetic Data—0
A Real-Time DETR Approach to Bangladesh Road Object Detection for Autonomous Vehicles—0
Enhancing Autonomous Driving Safety through World Model-Based Predictive Navigation and Adaptive Learning Algorithms for 5G Wireless Applications—0
Physically Interpretable Probabilistic Domain Characterization—0
Experimental comparison of graph-based approximate nearest neighbor search algorithms on edge devices—0
FedRAV: Hierarchically Federated Region-Learning for Traffic Object Classification of Autonomous VehiclesCode0
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Benchmark Results

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