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 1771–1780 of 2605 papers

TitleStatusHype
Learning Image Attacks toward Vision Guided Autonomous Vehicles—0
Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy—0
Challenges and Obstacles Towards Deploying Deep Learning Models on Mobile Devices—0
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet AutoencoderCode0
Calibration of Human Driving Behavior and Preference Using Naturalistic Traffic Data—0
Enabling 3D Object Detection with a Low-Resolution LiDAR—0
Situational Coverage and Rate Distribution Maps for 5G V2X Systems Using Ray-Tracing—0
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous DrivingCode1
Lane Graph Estimation for Scene Understanding in Urban DrivingCode1
Pedestrian Collision Avoidance for Autonomous Vehicles at Unsignalized Intersection Using Deep Q-Network—0
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Benchmark Results

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