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 781–790 of 2605 papers

TitleStatusHype
Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles—0
Semi-Supervised 3D Object Detection with Channel Augmentation using Transformation Equivariance—0
Cross Dataset Analysis and Network Architecture Repair for Autonomous Car Lane Detection—0
Driving with Prior Maps: Unified Vector Prior Encoding for Autonomous Vehicle Mapping—0
ICPR 2024 Competition on Safe Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather Conditions—0
Multi-V2X: A Large Scale Multi-modal Multi-penetration-rate Dataset for Cooperative PerceptionCode0
Vehicular Resilient Control Strategy for a Platoon of Self-Driving Vehicles under DoS Attack—0
Local Map Construction with SDMap: A Comprehensive Survey—0
LASP: Surveying the State-of-the-Art in Large Language Model-Assisted AI Planning—0
Surveying You Only Look Once (YOLO) Multispectral Object Detection Advancements, Applications And Challenges—0
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Benchmark Results

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