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 861–870 of 2605 papers

TitleStatusHype
Towards stable training of parallel continual learningCode0
Real-Time Anomaly Detection and Reactive Planning with Large Language Models—0
CommRad: Context-Aware Sensing-Driven Millimeter-Wave Networks—0
LSM: A Comprehensive Metric for Assessing the Safety of Lane Detection Systems in Autonomous Driving—0
Invisible Optical Adversarial Stripes on Traffic Sign against Autonomous Vehicles—0
NDST: Neural Driving Style Transfer for Human-Like Vision-Based Autonomous Driving—0
A Neurosymbolic Approach to Adaptive Feature Extraction in SLAM—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
MapsTP: HD Map Images Based Multimodal Trajectory Prediction for Automated Vehicles—0
Object-Oriented Material Classification and 3D Clustering for Improved Semantic Perception and Mapping in Mobile RobotsCode0
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Benchmark Results

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