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 1401–1410 of 2605 papers

TitleStatusHype
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning—0
Improving Deep Dynamics Models for Autonomous Vehicles with Multimodal Latent Mapping of Surfaces—0
ADCNet: Learning from Raw Radar Data via Distillation—0
Infrastructure-based End-to-End Learning and Prevention of Driver Failure—0
Quantifying the Value of Preview Information for Safety Control—0
Social Occlusion Inference with Vectorized Representation for Autonomous Driving—0
Trajectory-Prediction with Vision: A Survey—0
Probabilistic Uncertainty-Aware Risk Spot Detector for Naturalistic Driving—0
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving—0
Sequential Spatial Network for Collision Avoidance in Autonomous Driving—0
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Benchmark Results

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