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 1211–1220 of 2605 papers

TitleStatusHype
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation—0
Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review—0
Automatic Traffic Sign Detection and Recognition Using SegU-Net and a Modified Tversky Loss Function With L1-Constraint—0
A Multiclass Simulation-Based Dynamic Traffic Assignment Model for Mixed Traffic Flow of Connected and Autonomous Vehicles and Human-Driven Vehicles—0
Adaptive Stress Testing for Autonomous Vehicles—0
A CASE STUDY ON OPTIMAL DEEP LEARNING MODEL FOR UAVS—0
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review—0
Deep learning based infrared small object segmentation: Challenges and future directions—0
Automatic Testing With Reusable Adversarial Agents—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
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Benchmark Results

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