SOTAVerified

Autonomous Driving

Autonomous driving is the task of driving a vehicle 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: Exploring the Limitations of Behavior Cloning for Autonomous Driving)

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5076–5100 of 6092 papers

TitleStatusHype
Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor—0
RGB cameras failures and their effects in autonomous driving applicationsCode1
Visual Localization for Autonomous Driving: Mapping the Accurate Location in the City Maze—0
DAWN: Vehicle Detection in Adverse Weather Nature Dataset—0
Balanced Depth Completion between Dense Depth Inference and Sparse Range Measurements via KISS-GP—0
Estimating the Magnitude and Phase of Automotive Radar Signals under Multiple Interference Sources with Fully Convolutional NetworksCode1
Reinforced Wasserstein Training for Severity-Aware Semantic Segmentation in Autonomous Driving—0
Measures of Complexity for Large Scale Image Datasets—0
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving—0
Robot Action Selection Learning via Layered Dimension Informed Program SynthesisCode0
Rethinking 3D LiDAR Point Cloud SegmentationCode0
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty—0
LiDAR Data Enrichment Using Deep Learning Based on High-Resolution Image: An Approach to Achieve High-Performance LiDAR SLAM Using Low-cost LiDAR—0
VPC-Net: Completion of 3D Vehicles from MLS Point CloudsCode1
A Sensitivity Analysis Approach for Evaluating a Radar Simulation for Virtual Testing of Autonomous Driving Functions—0
Graph Signal Processing for Geometric Data and Beyond: Theory and Applications—0
Active Perception using Light Curtains for Autonomous Driving—0
Comparison of Source Coding Techniques for the Vehicle to Vehicle Communication—0
A Comparative Analysis of Deep Reinforcement Learning-enabled Freeway Decision-making for Automated Vehicles—0
PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving—0
Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving ValidationCode0
Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications—0
S³Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data—0
Deep Material Recognition in Light-Fields via Disentanglement of Spatial and Angular Information—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95—Unverified
2InterFuserDriving Score76.18—Unverified
3TCPDriving Score75.14—Unverified
4TF++ WPDriving Score66.32—Unverified
5Learning From All Vehicles (LAV)Driving Score61.85—Unverified
6TransFuserDriving Score61.18—Unverified
7TransFuser (Reproduced)Driving Score55.04—Unverified
8TCP (Reproduced)Driving Score47.91—Unverified
9Latent TransFuserDriving Score45.2—Unverified
10GRIADDriving Score36.79—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17—Unverified
2TransFuserRC56.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91—Unverified
2TransFuserRC78.41—Unverified