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 971–980 of 2605 papers

TitleStatusHype
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator—0
Benefits of V2V communication in connected and autonomous vehicles in the presence of delays in communicated signals—0
Voice-Assisted Real-Time Traffic Sign Recognition System Using Convolutional Neural Network—0
Depth Estimation using Weighted-loss and Transfer Learning—0
Monocular 3D lane detection for Autonomous Driving: Recent Achievements, Challenges, and Outlooks—0
Enhanced Cooperative Perception for Autonomous Vehicles Using Imperfect Communication—0
Incorporating Explanations into Human-Machine Interfaces for Trust and Situation Awareness in Autonomous Vehicles—0
Label-Efficient 3D Object Detection For Road-Side Units—0
Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenes—0
The Open Autonomy Safety Case Framework—0
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Benchmark Results

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