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 1621–1630 of 2605 papers

TitleStatusHype
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization—0
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios—0
Optimal Lane-Free Crossing of CAVs through Intersections—0
MTANet: Multitask-Aware Network With Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding—0
Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling—0
FoV-Net: Field-of-View Extrapolation Using Self-Attention and Uncertainty—0
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems—0
In Rain or Shine: Understanding and Overcoming Dataset Bias for Improving Robustness Against Weather Corruptions for Autonomous Vehicles—0
Bi-directional Loop Closure for Visual SLAM—0
A Convex Optimal Control Framework for Autonomous Vehicle Intersection Crossing—0
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Benchmark Results

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