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 811–820 of 2605 papers

TitleStatusHype
Diffusion-Based Particle-DETR for BEV Perception—0
Robust Stochastic Graph Generator for Counterfactual Explanations—0
Scope Compliance Uncertainty EstimateCode0
Beyond Empirical Windowing: An Attention-Based Approach for Trust Prediction in Autonomous Vehicles—0
A Case Study of Image Enhancement Algorithms' Effectiveness of Improving Neural Networks' Performance on Adverse Images—0
NeuroFlow: Development of lightweight and efficient model integration scheduling strategy for autonomous driving system—0
Personalized Autonomous Driving with Large Language Models: Field ExperimentsCode1
Reliability in Semantic Segmentation: Can We Use Synthetic Data?Code1
Challenges of YOLO Series for Object Detection in Extremely Heavy Rain: CALRA Simulator based Synthetic Evaluation Dataset—0
Optimization of Power Control for Autonomous Hybrid Electric Vehicles with Flexible Power Demand—0
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Benchmark Results

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