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 2471–2480 of 2605 papers

TitleStatusHype
Towards a Fatality-Aware Benchmark of Probabilistic Reaction Prediction in Highly Interactive Driving Scenarios—0
Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning—0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
JuncNet: A Deep Neural Network for Road Junction Disambiguation for Autonomous Vehicles—0
Baidu Apollo Auto-Calibration System - An Industry-Level Data-Driven and Learning based Vehicle Longitude Dynamic Calibrating AlgorithmCode0
Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous Vehicles—0
Autonomous Driving without a Burden: View from Outside with Elevated LiDAR—0
A Brief Survey and an Application of Semantic Image Segmentation for Autonomous Driving—0
Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios—0
Vehicles Lane-changing Behavior Detection—0
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Benchmark Results

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