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 1051–1060 of 2605 papers

TitleStatusHype
Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea—0
SemTra: A Semantic Skill Translator for Cross-Domain Zero-Shot Policy Adaptation—0
Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets—0
Improved Generalizability of CNN Based Lane Detection in Challenging Weather Using Adaptive Preprocessing Parameter Tuning—0
Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning—0
Driving Everywhere with Large Language Model Policy Adaptation—0
Savvy: Trustworthy Autonomous Vehicles Architecture—0
AINS: Affordable Indoor Navigation Solution via Line Color Identification Using Mono-Camera for Autonomous Vehicles—0
V2VSSC: A 3D Semantic Scene Completion Benchmark for Perception with Vehicle to Vehicle Communication—0
Robust Data-EnablEd Predictive Leading Cruise Control via Reachability Analysis—0
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Benchmark Results

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