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 481–490 of 2605 papers

TitleStatusHype
Areas of Improvement for Autonomous Vehicles: A Machine Learning Analysis of Disengagement Reports—0
MSMA: Multi-agent Trajectory Prediction in Connected and Autonomous Vehicle Environment with Multi-source Data IntegrationCode1
Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving—0
Pixel-Level GPS Localization and Denoising using Computer Vision and 6G Communication Beams—0
RePLAy: Remove Projective LiDAR Depthmap Artifacts via Exploiting Epipolar Geometry—0
Large Language Models for Human-like Autonomous Driving: A Survey—0
Adaptive Target Tracking Using Retrospective Cost Input Estimation—0
FH-DRL: Exponential-Hyperbolic Frontier Heuristics with DRL for accelerated Exploration in Unknown Environments—0
CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions—0
Personalized and Context-aware Route Planning for Edge-assisted Vehicles—0
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Benchmark Results

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