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 1971–1980 of 2605 papers

TitleStatusHype
Targeted Physical-World Attention Attack on Deep Learning Models in Road Sign RecognitionCode0
Learning to Localise Automated Vehicles in Challenging Environments using Inertial Navigation Systems (INS)—0
Automotive Radar Data Acquisition using Object DetectionCode0
6G Cellular Networks and Connected Autonomous Vehicles—0
Facilitating Connected Autonomous Vehicle Operations Using Space-weighted Information Fusion and Deep Reinforcement Learning Based Control—0
The Development of Visualization Psychology Analysis Tools to Account for Trust—0
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
VATLD: A Visual Analytics System to Assess, Understand and Improve Traffic Light Detection—0
Towards a Systematic Computational Framework for Modeling Multi-Agent Decision-Making at Micro Level for Smart Vehicles in a Smart World—0
A Generic Framework for Clustering Vehicle Motion Trajectories—0
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Benchmark Results

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