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 2571–2580 of 2605 papers

TitleStatusHype
Learning to Map Vehicles into Bird's Eye ViewCode0
End-to-end Learning of Image based Lane-Change DecisionCode0
Pedestrian Prediction by Planning using Deep Neural Networks—0
Fine-grained acceleration control for autonomous intersection management using deep reinforcement learning—0
LiDAR-Camera Calibration using 3D-3D Point correspondencesCode0
VANETs Meet Autonomous Vehicles: A Multimodal 3D Environment Learning Approach—0
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks—0
Navigating Occluded Intersections with Autonomous Vehicles using Deep Reinforcement Learning—0
Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art—0
Finite-Time Stabilization of Longitudinal Control for Autonomous Vehicles via a Model-Free Approach—0
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Benchmark Results

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