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 501–510 of 2605 papers

TitleStatusHype
Risk-Aware Vehicle Trajectory Prediction Under Safety-Critical Scenarios—0
PG-Attack: A Precision-Guided Adversarial Attack Framework Against Vision Foundation Models for Autonomous DrivingCode1
VisionTrap: Vision-Augmented Trajectory Prediction Guided by Textual Descriptions—0
Data selection method for assessment of autonomous vehiclesCode0
ParCon: Noise-Robust Collaborative Perception via Multi-module Parallel Connection—0
Communication-Aware Reinforcement Learning for Cooperative Adaptive Cruise Control—0
CommRad: Context-Aware Sensing-Driven Millimeter-Wave Networks—0
Real-Time Anomaly Detection and Reactive Planning with Large Language Models—0
Towards stable training of parallel continual learningCode0
NDST: Neural Driving Style Transfer for Human-Like Vision-Based Autonomous Driving—0
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Benchmark Results

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