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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 611–620 of 2605 papers

TitleStatusHype
DeepCrashTest: Turning Dashcam Videos into Virtual Crash Tests for Automated Driving Systems—0
DeepFault: Fault Localization for Deep Neural Networks—0
DeepiSign: Invisible Fragile Watermark to Protect the Integrityand Authenticity of CNN—0
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation—0
Deep Reinforcement Learning for Autonomous Vehicle Intersection Navigation—0
A Multi-Agent Reinforcement Learning Approach For Safe and Efficient Behavior Planning Of Connected Autonomous Vehicles—0
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning—0
Behavior Identification and Prediction for a Probabilistic Risk Framework—0
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving—0
A Near Sensor Edge Computing System for Point Cloud Semantic Segmentation—0
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Benchmark Results

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